One Year of MCP — with David Soria Parra and AAIF leads from OpenAI, Goose, Linux Foundation

27 Dec 2025 · 1 h 39 min · 41 chapters

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Latent Space Podcast Episode Notes

Episode Title

One Year of MCP — with David Soria Parra and AAIF Leads from OpenAI, Goose, Linux Foundation

Overview This episode celebrates the one-year anniversary of the Model Context Protocol (MCP), launched by Anthropic. MCP has rapidly evolved into a widely adopted standard for agentic AI systems and is now part of the newly formed Agentic AI Foundation (AAIF). The discussion features key figures from Anthropic, OpenAI, Block (Goose), and the Linux Foundation, reflecting on the journey of MCP, its implications for the industry, and the future of agentic AI.

Key Contributors

  • David Soria Parra (MCP Lead, Anthropic)
  • Nick Cooper (OpenAI)
  • Brad Howes (Block, Goose)
  • Jim Zemlin (CEO, Linux Foundation)

---

Introduction

  • Background:
  • The MCP was introduced as an open standard for connecting AI applications to necessary data and tools.
  • Significant adoption by major companies (OpenAI, Microsoft, Google).
  • Transition to the AAIF under the Linux Foundation to ensure neutrality and proper governance.

---

MCP's Journey

  • Initial Adoption:
  • Growth began during the Thanksgiving and Christmas period with early adopters such as Cursor and VS Code.
  • Major endorsements from tech leaders (Sam Altman, Satya Nadella, Sundar Pichai) catalyzed further adoption.
  • Protocol Evolution:
  • Transition from local-only servers to remote MCP servers.
  • Introduction of OAuth 2.1 for authentication, addressing enterprise needs.
  • Continuous improvements based on enterprise feedback.

Key Features Discussed

  • Long-running Tasks:
  • Introduced to support asynchronous operations and deep research capabilities.
  • MCP Apps (iframes):
  • Enabling richer user interfaces for AI applications.
  • Addressing the need for better user interactions beyond text-based interfaces.

---

Increasing Internal Adoption

  • Enterprise Use Cases:
  • Enterprises utilize MCP for internal agents connecting to various services (e.g., Slack, proprietary data).
  • Authentication Challenges:
  • Evolution from a combined authentication and resource server to a more flexible design, separating these concerns for better enterprise integration.

---

Technical Aspects of MCP

  • Transport Layer and Scalability:
  • Challenges faced with HTTP streaming and the need for a robust transport layer for agent-to-agent communication.
  • Community Building:
  • Importance of fostering a developer community around MCP and encouraging contributions to the protocol.

Future Developments

  • Registry Exploration:
  • The need for an official registry for MCP servers and potential for sub-registries to curate trusted resources.
  • Open Source Collaboration:
  • The foundation aims to curate a diverse range of projects that complement MCP, enhancing interoperability and collaboration across the agentic AI landscape.

---

Closing Reflections

Highlights from the Discussion

  • Neutrality and Openness:
  • Emphasizing the importance of maintaining the open and neutral nature of MCP within the foundation.
  • Community Engagement:
  • Encouraging developers to participate actively in the MCP ecosystem, contributing to SDK development and feedback loops.
  • Long-term Vision:
  • Aspirations for MCP to evolve into a communication layer for asynchronous agents that enhance productivity.

---

Conclusion The episode concludes with a call to action for developers to engage with MCP, emphasizing the ongoing commitment from Anthropic and the broader community to drive the future of agentic AI forward. The exciting prospects of the AAIF and the collaborative nature of the foundation highlight an optimistic future for AI standards.

Full video and more details on the episode can be found at [Latent Space](https://latent.space).

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

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Anniversary Reflections

0:45 to 1:40

A recap of the one-year anniversary of MCP and its celebration.

“I would say in terms of my food bench, Anthropic does rank over OpenAI.”

Growth and Adoption of MCP

1:40 to 3:12

Discussion on the rapid growth and major clients adopting MCP over the year.

“And then like you had this like inflection point around April with like Sam Altman and Satya and Sundar and all posting about like MCP and that they're going to adopt MCP at Microsoft, at Google, at OpenAI.”

Protocol Improvements and Challenges

3:12 to 4:28

Overview of improvements made to the MCP protocol and associated challenges.

“you know, maybe even agent to agent communication.”

Foundation Goals and Protocol Standards

4:28 to 5:59

Discussion on the goals of the Agentica Foundation and its approach to protocols.

“and making sure we're learning along the ways and being able to like shepherd this in the way we feel is best for the industry together with OpenAI and Block.”

MCP Development and Community Insight

5:59 to 6:52

Explores the development of MCP and the community's contribution to its evolution.

Authentication and Security Protocols

6:52 to 9:50

In-depth discussion on authentication challenges and security improvements in MCP.

“But I think, like, every single time you've actually managed to, like, focus on something important.”

Transport Protocols and Lessons Learned

9:50 to 14:03

Insights on transport protocols used in MCP and key lessons from past implementations.

“oh, in the morning, I'm going to go log in with Google and then get access to all my work stuff, right?”

Challenges of Horizontal Scaling in AI Systems

14:03 to 14:57

Learn about the complexities of horizontal scaling in AI applications.

“Like some form usually pops up or something like that.”

Consensus in High-Stakes Engineering Meetings

14:58 to 16:58

Discover how consensus is reached among senior engineers from top companies.

“And I think we're just allowed to find the right solutions, but it's just complicated.”

IETF vs. Private Group Standards Processes

16:59 to 18:30

Explore the differences between IETF and private group processes for standards.

“So I'm very grateful to be in this situation.”
Show all 41 chapters

Influence of Model Improvements on Protocol Design

18:31 to 20:54

Understand how model advancements affect protocol development in AI.

“of like the model improvements with how to shape the protocol?”

Understanding MCP and Tool Calling

20:55 to 23:10

Learn about the MCP protocol and how it facilitates tool calling in AI.

“Yeah, and I think the, yeah, the context fraud point is important.”

Distinguishing Between MCP and Skills

23:11 to 25:58

Clarify the distinctions between the MCP protocol and skills in AI.

“I only bring it up because it's mentally linked in my mind to progressive disclosure and to adding preset code scripts and all that.”

Internal Usage of MCP in Organizations

25:59 to 28:00

Discover how organizations utilize MCP for their internal applications.

“And I think that's actually a really fun model.”

The Origin Story of MCP

28:00 to 30:16

Learn about the initial motivations and growth of the MCP project.

“around like how we feel, about the company, about the future, about AI, about safety, these type of things.”

Building and Managing MCP Servers

30:16 to 33:12

Explore the infrastructure and management practices for MCP servers in enterprises.

“recently a very great blog post about like a lot of the usage of mcp you're actually seeing is internal in companies.”

The Need for Centralized Registries

33:12 to 35:58

Understand the importance of centralized registries for MCP servers and their trust issues.

“I think that's something that didn't exist before, right?”

Lessons from Financial Services Events

35:58 to 39:22

Gain insights from the financial services sector regarding MCP implementation.

“And I think that's really the interesting ground where we want to experiment.”

Current Use Cases and Future Aspirations

39:22 to 42:00

Examine current use cases of MCP and discuss future possibilities for task automation.

“That's always the, you know, last time we talked about this.”

Designing Long-Running Tasks in AI

42:00 to 44:00

Explore the challenges and design considerations for implementing long-running tasks in AI systems.

“or what we're going to call MCPI in the future.”

The Evolution of Asynchronous Operations

44:00 to 46:00

Learn about the evolution and importance of asynchronous operations in AI applications.

“And a pure asynchronous tool call would just not do this.”

Context Management and Compression Techniques

46:00 to 48:00

Discuss methods for managing context and implementing context compression in AI systems.

“In the end of the day, it's designed like a classic operating system, interface, like you create a task, you pull it until it's done.”

MCP as an Application Layer Protocol

48:00 to 50:00

Understand how MCP functions as an application layer protocol for AI applications.

“One minor thing, and so let's say super long-running pass.”

Developer Perspectives on MCP

50:00 to 52:00

Examine how developers can utilize MCP for building AI applications and its significance in the tech ecosystem.

“A year ago, everybody would have told you it's RAG style stuff, but it's now apparently dead, right?”

User Interface Innovations for AI Tools

52:00 to 54:00

Delve into the need for enhanced user interfaces in AI applications for better user experience.

“And in that regard, more like on the consumer focus side.”

UI Challenges and Iteration in MCP Development

56:00 to 56:52

Discussion on the importance of UI design in MCP and the need for iterative development.

“That's why I don't think it should be an iframe long-term.”

MCP Extensions and Governance

56:52 to 58:12

Exploration of the technicalities and governance surrounding MCP extensions and their implications.

“But the other solution to the problem is the IGI build approach of just give it a tool that says, give me a style sheet.”

Building Secure MCP Servers

58:12 to 1:00:16

Discussion on the importance of security in MCP servers and the need for guarantees in handling sensitive data.

“We're going to look into like financial services as an extension.”

Community Engagement and Building with MCP

1:00:16 to 1:02:36

Encouragement to engage with the MCP community and build better servers and SDKs.

“being in the Discord channel, talking with us, giving us ideas, while also just helping us implementing like the TypeScript SDKs, the Python SDKs.”

Commitment to Open Standards in MCP

1:02:36 to 1:03:28

Reassurance of the commitment to maintaining MCP as an open and neutral protocol.

“I think that's the that's the other part to that.”

Origins of the AAIF and MCP Collaboration

1:03:44 to 1:06:08

Discussion on how the collaboration between AAIF and MCP began and its evolution.

“I've been working there 22 years, and I was the person who helped facilitate the launch of the foundation, but take no credit for any of the technology work.”

The Role of the Linux Foundation in MCP

1:06:08 to 1:10:06

Exploration of how the Linux Foundation supports and structures the MCP ecosystem.

“And so just a lot of conversation, like what do we want to do?”

Navigating Governance and Technical Contributions

1:10:06 to 1:18:19

Learn how the Lynx Foundation is addressing governance and technical contributions amidst increased interest.

“It's like the first thing we need to like define some structure and work out what we, like how to bring it all together.”

The Role of Composability in Agentic Systems

1:18:20 to 1:22:18

Discover the importance of composability and collaboration in the development of agentic systems.

“One principle that really comes to mind to me is composability.”

The Incentives for Project Collaboration

1:22:19 to 1:24:01

Understand the motivations for contributing projects to the foundation and the benefits of collaboration.

“feedback and kind of a positive feedback loop of great project that gets great products in the market.”

The Need for a New Foundation in AI

1:24:01 to 1:26:38

Explore why a new foundation is essential for the evolving AI landscape.

“LF has many other funds and organizations including Data and AI Foundation as well as dedicated PyTorch and all the other ones I guess why a new foundation?”

Foundation Investments and Community Engagement

1:26:39 to 1:30:48

Learn about how funds are directed and the importance of community engagement.

“But everything's about growth and evolution.”

Comparative Insights from CNCF to MCP

1:30:49 to 1:34:49

Understand the parallels between the Cloud Native Computing Foundation and the new MCP initiative.

“That's where the funding goes for these kind of things.”

Anticipating the Future of the Foundation

1:34:50 to 1:37:18

Discuss the potential future developments and contributions of the new foundation.

“We don't want to keep you guys too long.”

Exciting Prospects for Agentic Technology

1:37:19 to 1:38:00

Explore the excitement around asynchronous agents and their potential applications.

“You don't enjoy pressing yes every five?”

Anticipating Success Stories in Agentic Technology

1:38:00 to 1:39:01

Explore the potential impact and success stories of agentic technology in various organizations.

“I think what I look forward to is, you know, the success stories of, you know, the organization that's implemented agentic technology in that way and hearing how it really impacted their business.”
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Transcript

Automatic transcript. May contain errors.

0:06Hey, everyone. Welcome to the Layden Space Podcast. This is Alasio, founder of Kernel Labs, and I'm joined by SWIX, editor of Blade & Space. Hey, and here we are joined, finally in the studio, for the first time. Welcome back, David, from Anthropics slash MCP. Yeah, hey, well, nice to finally talk to you in Perth. And last time, like a year ago, it was over VC, and this is way fun. I watched it back, it was eight months. It's been a crazy eight months, and I think we just celebrated like the one-year anniversary of MCP. Yes, we did. At least the public announcement. Yeah. And also last night or yesterday was the Agentic AI.

0:40Foundation launch. Yeah, that was nice. It was a nice event. It was nice to see the Anthropic office. Yeah. And I've been. You like it? Yeah. It's very good food. I would say in terms of my food bench, Anthropic does rank over OpenAI. Yeah. At least that's what we have going for us. Awesome, man. Do you want to give just a quick overview of what's happening with MCPA and how you're donating it to the foundation and then we'll do kind of like a one-year recap of the protocol itself. And then we'll have the rest of the leads from the foundation join us to do more of the high level. Yeah, yeah, that sounds good.

1:16Yeah, I mean, where we're at at the moment, we have done like a year, like a year ago we launched it and then we had this like crazy adoption over the last year now, which it feels like an eternity, honestly. But we have this like crazy growth and like adoption, you know, through initially through like Thanksgiving and Christmas very early with a lot of like builders building MCP. And then, you know, you had like the first big clients coming in like Cursor and VS Code. And then like you had this like inflection point around April with like Sam Altman and Satya and Sundar and all posting about like MCP and that they're going to adopt MCP at Microsoft, at Google, at OpenAI.

1:59And that was really like the big inflection point. But in all of the time, you also had to do a lot of work on the protocol itself. We launched originally as basically local only. We could build local MCP servers for Cloud Desktop. But then in March this year, we moved into how can you do remote MCP servers to connect to a remote server and introduced the first iteration of authentication. And then in June, we revisited that and improved it quite a little bit so that it works better for, you know, for enterprises in particularly. And we were very, very lucky that in that time for March, like June, we're like able to like have absolute industry leading experts that literally work on OAuth itself to help us with some of the pieces, right?

2:49And how to get it right. And then we focused a lot of on like security best practices and this type of work. And now we like have, I feel we have a really solid foundation and we're doing, we just launched like in our end of like November, then the recent iteration of the protocol, finally like the next bigger improvement to the protocol, which is like long running tasks to really allow for like, you know, deep research type of task and like, you know, maybe even agent to agent communication. And so I think we're just stepping into like this territory now with like, okay, we have really solid foundations.

3:22We have like one more big primitive we want to add. We want to make like a little bit more scalability. things work and then we're you know gonna get into a phase where it probably becomes a bit more stable and so yeah it's been an absolutely crazy year man you did say the agent to agent so there is an A2A protocol I'm curious when the Agentica Engineering Foundation got formed or just Agentica Foundation was there any discussion about any of these other protocols being a part of it or you know Sean wrote a post called YMCP1 already so maybe it was already And it was before Sev and all the other guys.

4:00Yeah, you were right. I mean, I think it was just obvious that it was going to happen. Yeah. So we of course have conversations around what else is in the market, like the payment protocols that are interesting and so on. But when we wanted to start a foundation, we wanted to make sure, first of all, two things. We wanted to start small and make sure that the group that is founding this, for us, it's the first time we as Anthropic have an open source foundation. So this is all new to us. So we really want to start it small and making sure we're learning along the ways and being able to like shepherd this in the way we feel is best for the industry together with OpenAI and Block.

4:38But the second part of that is also like we really felt like we wanted to see things that have a lot of adoption or de facto like, at least on the protocol side, like a de facto standard. And I don't think any of the other protocols, it feels like they're not just there yet. But of course, if they get there, then we're like super open as long as they're like complementary to what's in the foundation. On the application side, we're a little bit more flexible and we're like more open. But on the protocol side, I think we really want to make sure that we're not like offering like, the foundation doesn't encompass like five protocols for the same like communication there.

5:16And so, yeah, there was discussion, but I think for now, we just want to start it small. Is there a role, like a double head that you have now with the foundation or are you more focused on mcp i am still mostly focused on mcp it's a bit of a double head so there is just like i think people need to understand like the foundation part is mostly just an umbrella to make sure the projects under it stay always neutral and i think that's really the most important part you want to get a lot you know want to understand because the rest of it is like okay how do we use the budget of the foundation for events and things that are like quite dry and then the technical parts to like mcp they stay actually the same like on the on the way we govern mcp nothing has really changed and so that's really still my job as the lead core maintainer of like shepherding um the process that is shepherding the protocol forward and then beyond that now the additional double role is like i'm also going to be on the technical steering committee of the foundation which will like make sure to like figure out what are the projects we want to have in the foundation so if someone comes with a project to us the people that have projects in it will decide is this something we would want is this something that we feel is like well maintained has a lot of adoption it's not going to go away we want to make sure the foundation is have like super interesting and important projects and not like a dumping ground like have you know some foundations might have ended up with that's true uh so we're going to meet some of the others later but maybe we'll just focus back on the sort of mcp development yeah you covered a lot there's been four spec releases that's a lot yeah that you said people may have missed some of them that's what i'm saying right like and i think it's really interesting how uh you're we've continued to work on like really important parts like i always think like it's very hard to follow up a major success with a sequel yeah Because the SQL usually, like, it's hard to repeat that impact.

7:10But I think, like, every single time you've actually managed to, like, focus on something important. Yeah. So maybe we can cover, I guess, maybe we'll start with the March-May one, which is HTTP streaming, which is good, and the off-spec. Yeah. Any other, I don't know if you want to highlight any others, but we'll just catch people up on that stuff. Yeah, so that was, I think that was really a, that was such an important one. It was the number one requested thing. Yeah, it was like, it really opened up this like remote thing. And we already knew actually in December, in November, that the next big thing will be like, how can you do this over remote?

7:45Authentication is quite important. One of the things I think people very rarely notice when it comes to MCP, MCP is very prescriptive in like each layer. Like other protocols are not like that, for example. Like we like, you want to do authentication. If the client and the server don't know each other, you need to do OAuth, right? And so we were very early, we wanted to have like one way to do something. And so we really focused on like, what does this mean? Like, how do we get it over? How do we build a protocol that has this like these streaming properties that we require? And then how do we do authentication very early?

8:20Authentication, in the first iteration, I think we did an okay job, but we got some aspects wrong. And most of them, honestly, were just me not understanding enterprises well enough. But then again, I think the strengths that we have with MCP, And I think the one thing, if anything, I'm proud of is like building a community of people that can come together and help me figure shit out. Because, you know, I have my set of experiences of like what I'm good at. And enterprise authentication, it turns out, is not one of them. Right. But they're way better suited people for that. And so that's when we like, I feel that's more.

8:52I saw you post that, but I didn't really dig into the details. Was it like the typical SAML type of authentication issue? The main issue we did is in OAuth, there are two components. There is an authentication server who gives you the token, and then there's the resource server. It takes the token and gives you the resource in return. And in the first iteration of our authentication spec, we combined them together into the MCP server, which if you were building... Unusable, yeah. It's kind of usable if you build an MCP server like as like a public server, as a, you know, you're a startup, you're building a server for yourself.

9:30You want to bind this to the accounts you already have. That is completely usable. The reality in enterprises is you don't authentic, you authenticate with some central entity. Like, you know, you have some IDP provider, an IDP, and you go off to NL0. Yeah. For most people, they don't even notice that it's happening. All they know is like, oh, in the morning, I'm going to go log in with Google and then get access to all my work stuff, right? But that's effectively the IDP, right? And if you combine these into the same server, you just can't do this anymore. And so all we needed to do is like, okay, we are a resource server.

10:06The MSP server is a resource server. How you get the token from the authentication server, we have opinions on how you should do it, but it's kind of separated. And that's what happened then in the doing spec where we separated this out and worked through a lot of these like, okay, now how do you do dynamic client registration and other aspects, which also were part of the March spec. we can talk about that that's a whole other story of like we are actually pushing the boundaries of what a wealth can do with with mcp because we're trying something very unique with mcp um but yeah that was that was the big part in in march which we like and that was that authentication spec the first iteration then fixing it in june yeah what's the state of agents authenticating on my behalf because even today with the oa i still have to you know log into linear and whatnot yeah wealth OAuth itself is for the most part a very human-centric protocol.

10:55It just tells you how you obtain a token if you don't have a token. Once you have a token, actually, it doesn't matter. You just put it into the bearer token. And so we're not very prescriptive of what agent-to-agent authentication would look like on behalf of agents. There are ideas that we're looking into, and I don't have all the specifics, but we're not prescriptive in the same way we're prescriptive as with OAuth. but you can technically, at the moment you have a token that might be like bound to like a workload identity or something like that, then you just can pass that still to the MCP server.

11:27We're just not telling you how to obtain it just yet. And so we're not prescriptive. And so people do this and they can do it particularly when they're within like an enterprise and have a somewhat closed ecosystem. But if the client and the server don't know each other, we just don't have a good solution for now. And then yeah, on the remote thing, you went from local servers like SSC and then streamable HTTP, to be any learnings you want to call out there any uh yeah regrets or uh learnings for others and transport the one discussion has never stopped from the very beginning of the last years about transport and we literally just spent the last two days at the google offices with a bunch of like scene engineers from google microsoft aws anthropic opening eye just like what do we need to do here to really, really make this solid.

12:13When we looked into Mark, we wanted to get a transport going that basically retains a lot of the properties we had from standard IO because we really, and I still believe this until today, that MCP should also enable agents and agents are inherently somewhat stateful and there's some form of like long-term communication going between like the client and the server. And so we always looked for something like that. we also knew that we looked into alternatives like okay what happens if you do web sockets for example and we have found a lot of issues with doing a proper bidirectional stream and we're like okay what is the right middle ground between having something that can be used in the simplest form that people do like where they just want to provide a tool but then is able to be upgraded to like a full bidirectional stream if you need it because you really have like complex agents communicating with each other.

13:05That's where streamable HTTP was born with that intent. And I think there's something that in retrospect that we got right and something that we got wrong. I think we got right that we are really leaning just on standard HTTP in that regard. We got wrong that we made a lot of things optional for the clients to do. Like you can, the client can connect and open this return stream from the server, but it doesn't have to. And the reality is, no client does it because it's optional. And so a lot of the bidirectionality goes away. And so features like elicitations and sampling are just not available to servers because they don't have that stream open because the client implementer is like, ah, that's the minimal viable product for me.

13:47I don't have to do it. And so that became an issue. So I think there are lessons there. The second part of the lesson is that the way we designed the protocol, the transfer protocol requires some form of holding state on the server side. And that is fine if you have one server, but the moment you scale this horizontally across multiple pods and like in containers or something like that, well now if you get like true call and then elicitation and the elicitation result, you somehow require to like, you might hit two different servers and you need to find a way to have these two servers somehow get this result together and you effectively need some form of shared like the Redis, Memcache, whatever you want.

14:31Like some form usually pops up or something like that. You want to have like a shared state that you can like have. And that's kind of okay. And like we have seen this in PHP application and Python application being done. But it's not fun if you do this at scale. And we know from like some companies like the Googles of the world, the Microsoft of the world, they're doing MCP at a scale that I can't tell you the numbers, but it's like in a million of requests. And so now it becomes a problem, right? And so now we're sitting here like, okay, how do you build an installation of the protocol that allows for basically these principles of like making as simple as possible for simple MTP servers, but allow this full spectrum of like really bi-directional streaming if you need it, but also make it scalable.

15:15And I think we're just allowed to find the right solutions, but it's just complicated. yeah because a lot of the technology today is really just there's very little like that people either do the simple thing and then you do like something like rest or you do like a full by that stream and then you're just gonna do like web sockets or like gRPC and so on and we need kind of both what's it like to be in that kind of meeting where you have all these impressive companies and everyone is senior and everyone has an opinion that's much fun yeah i got to work with some of the best engineers in the industry.

15:48Like, it's insane. Okay, well, who decides, you know? Usually there's... We're trying to get to consensus. Like, the reality is technically I decide in the end of the day. But I think that's more like a formalism. In the end of the day, what you're trying to do is just to really narrow down of, like, what are the real problems which we all agree on? What are the things where we not necessarily agree on? And what are the, you know... And then within those bounds, like, build the best solution. And it takes a while. It takes a lot of iterations. But it's so much, honestly, it's so much fun because you get to see these unique problems from the companies.

16:27You see some of the identity of the companies in the problems themselves, right? Like, you know, Google has a different set of problems, like Microsoft. And a lot of it comes from, like, just the ways of building things. And then the problem from Anthropic looked different from the problem from OpenAI. But what I love about all of this is that everybody is, that like sometimes you step back and like you sit in a room with all these competitive companies, but you're actually building something together. And I love that. I've been in open source for like 25 years. Yeah, it's very, a lot of this kind of stuff.

16:57And when a standard works, this is the ideal. And these people are all amazing. I just learn from all my peers so much. So I'm very grateful to be in this situation. Yeah. This reminds me of the IETF standards process. is there some discussion about how this works as a private group versus something more traditional it's an interesting one like it does look a little bit like the itf the itf is very slightly different the itf is like an open forum where everybody can go and the result of that it's like the itf is very consensus-based and by accident not by like not necessarily because they want to be but by accident quite slow in the processes which is very good in many ways It's going to be undone, right?

17:38Right. Once it's up. Yeah. For example, when you look at the OLS 2.1 spec, it's been in the works for like three years or four years and they're just not done with it, right? And that's the length of which ITF standardization works. Like these things can take a long, long time. And I think that's good for certain pieces, but I think in AI at the moment, it's just so fast moving. You're somewhat forced to find a smaller group. And so that's why we run MCP as like a really traditional open source project with like a core maintainer group of like eight people that basically decide everything and then like input from everybody else.

18:12Like we get input and people can make suggestions and we have a lot of the changes don't come from the core maintainers, but they're the ones that decided. And that's like way more, it's like a middle ground of being somewhat consensus-based, but also somewhat like a bit of a dictatorship, which can be good if you want to move fast, which NCP wants to do at the moment. How do you balance the influence of like the model improvements with how to shape the protocol? Because obviously, you know, you have Anthropic and OpenAI, you guys are doing post-training on these models to make them better tool calling and you have preferences on the shape of the protocol versus there's people that are not aware of like how you're structuring that.

18:48So yeah, do you like share some of these? Like does the protocol influence some of the model post-training or like vice versa maybe? I'm not 100 % familiar. Like I'm a product person. I'm not fully familiar with everything we do on the research side for sure. but it influences the post-training in the sense that we're making use of things like the MCP Atlas, that we are having in our model cart of making sure that we're taking this large set of tools in the wild and make sure that our models work with that. But I think the primitives of the protocol, they're actually very rarely influenced by model improvements.

19:26I think there's a sense that we do anticipate the exponential that the models are on in terms of like improvement and that we're relying to some degree of mechanics that you can put into the model training. I'm going to get more concrete here. So, for example, people have had long conversations around context build of MCP servers. And that happens because MCP opens up the door to a lot of tools. and if you naively take all the tools or throw them into the context window, you just get a lot of bloat. It would be the equivalent if you take all the skills, take all the mockdown files and just throw them all into the context, you would also have a lot of bloat.

20:04But we already knew, and I think we always knew that you can do something like progressive discovery. And that's like a general principle thing of like you can give the model some information and let the model then decide to gain more information, right? And of course here is where we're like, some of the foresight that we see because we are the big model companies we know that we can train this if we wanted to and what the training does is just optimizes it the model can do it in principle already and any model can do it it does any type of tool calling but if you train the model for it it's just better at it and so these things then go hand in hand in a way but in the end of the day the general mechanic of progressive discovery that's just inherent to any type of model that can do any type of tool calling in the end of the day, if that makes sense.

20:55Yeah. Yeah, and I think the, yeah, the context fraud point is important. And I think down there's the MCP versus code mode. And then it's like, well, if Anthropic says code mode and Anthropic made MCP, maybe is that the best way? So the block was never actually called it code mode. That's the call fair term. That's it. But yeah, but like people call it, we call it pre-chromatic MCP and other call it code mode. In the end of the day, what it boils down to is just like, okay, and here's the interesting part. So first of all, MCP is a protocol between the AI application and servers, right? So the model is actually technically not involved in MCP.

21:30And so now you have an application go like, I have a bunch of tools. What can I do with it? And you can do the naive thing and go like, okay, I have tools. I'll throw them into tools for the model and I call them. But you can be more creative with it. You can go and like, okay, models are really good at writing code. What if I take this and treat it like API calls and you give it to the model and now the model generates, you know, code. And what you're effectively doing is this composability that the model would have done anyway by like call tool A, you know, get the result, go back to inference to call B and then combine it into call three.

22:06Now all you've done is you let the model optimize it in advance and put them into a bunch of code that is just executed in a sandbox and go like call one, put it into two, put the results into three, get a result. and all you've done is an optimization in the end of the day. But the benefits of MCP, of having authentication done for you, having something that is suited for the LLM, something that is automatically, that is discoverable and self-documenting, this thing has not gone away. That's still MCP for you, right? You're just using it at a different rate. So I'm always a little bit confused when people go like, but MCPs, why does it tell me that that doesn't mean MCPs use it?

22:43No, it's still just a different use, right? And I think you will see evolutions as we're getting better of like how we use these models and the infrastructure around it gets a bit more mature and you suddenly can assume that most model like AI applications will have some form of like sandboxing for execution. You can do a lot more fun stuff like that. But I don't think that the value of like a protocol that connects the model to the outside world is just gone because of it. That makes sense. I see it purely as an optimization, honestly, the token optimization. Is this a good time to bring up skills?

23:15Always. So awesome. So skills is a more recent concept. Yeah. I only bring it up because it's mentally linked in my mind to progressive disclosure and to adding preset code scripts and all that. Skills can also create skills, which is very fun. Yeah. Well, I think a lot of people are trying to place MCP versus skills. Obviously, they're not overlapping, but how do you view it? Yeah, I agree. I think that's the interesting part. They're not overlapping. I think they solve different things. I think skills are super great. And, you know, I think that the first that really like, they've been built from the principle is progressive discovery.

23:54But I think the mechanism of progressive discovery, that's just universal to any type of thing you can do with the model. But what skills do, they like, they give you the domain knowledge for like a specific set of tasks, like how you are, how you behave, how should the model behave as a data scientist or how should the model behave as an accountant or whatever. but MCP gives you the connectiveness of the actual actions that you can take with the outside world. And so I think they're somewhat orthogonal in terms of the skills really gives you this domain knowledge, just kind of vertical. And then MCP gives you this horizontal of like, okay, give me that one action.

24:32And of course, skills can take actions. They can take actions because you can have code and scripts in there. And that's great, but it has two interesting aspects that I think people got. The first one is you need an execution environment. So you need to use the way to execute. Your machine, yeah. Yes, and that's perfectly fine for, you know, if you like run a local, like, you know, cloud code or something. Then we can talk about like CLIs, for example. In those scenarios where you have like an execution environment, these things make a lot of sense. And then it's great. Or if you have a remote execution environment, then it makes a lot of sense.

25:04But you still don't get authentication in that regard. And so what I think NCP brings is the authentication piece. It brings the piece that you don't have to like an external person, like for example, if you have like a linear MTP server, they can improve the server. You don't have to deal with that in your skill, right? It's not fixed in space. And then the third part is that you don't necessarily need an execution environment because the execution environment is effectively somewhere else on the server. And so if you build a web application or like a mobile application, these things work better in some of these regards.

25:38So I think they are orthogonal in that regard for the most part. And I've seen some quite cool deployments where people use skills to explore different functions, the accountant, the engineer, the data scientist, and then use MCP servers to connect these skills to the actual data sources within the company. And I think that's actually a really fun model. And I think that's the closest how I think about this. Yeah, so MCP is the connectivity layer, I think is the word that you choose. The communication layer. communication later yeah so is it um architecturally i'm wondering if it's like the mcp's client inside of each skill or is there a shared client that can discover skills we do that as shared we do the shared one i think you technically want a bit more shared ones because you do the more shared you have the better the more you can do like discovery things you can do things like, okay, I have connection pooling.

26:38I have, I can do automatic discovery of things. I can even like, you know, in a skill, you might just very loosely describe what you want. And I can look into the registry that I have access to and get an MCP server for you, right? These things can you do, can do when you do it. But I think both works at the end of the day. Yeah, but this is things to experiment with. I do want to highlight for people who might've missed it. You said we do blah, blah, blah. Actually, I think nobody understands enough how much Anthropic Dog Foods MCP. And I only understood this when I watched John Welsh do his talk at AIE where he was like yeah we have MCP gateway everything goes through this.

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27:14Yeah. And like what can you say more about that? Yeah I mean like you know we use both right? We use a lot of like we use a lot of skills internally we use a lot of MCP search internally because like we have you know obviously you know you want to make it very easy for people to deploy MCP you want to like have some form of like integration with UIDPs and so on so we have a gateway that we've built custom purpose for ourselves and you just gotta like deploy your MCP servers. And it's all internal apps? It's all internal stuff. Yeah. Some of them are like external things, like technically external things, but in the lack of them offering a first party one, we have our own, like we have a Slack MCP server, which I love to use, that have Claude like summarize my Slack for me.

27:52And so there's quite a lot of usage for that. Like we even have like an MCP server, we're doing like a semi, a biannual like survey, for example, around like how we feel, about the company, about the future, about AI, about safety, these type of things. And we have an MCP server for that. And I can ask a lot of questions around the results, which is really fun. Is it your team maintaining it? No, we maintain it in a gateway. But I think one of the fun parts is when we started MCP, it was always, like MCP, before we even open-sourced it, it was born of the idea of like, I'm in a company that is growing crazy.

28:26I'm in the development side of things, development tooling side of things. I will grow slower than the rest how can I build something that they can all build for themselves and that's really the origin story of MCP and so it's fun to see a year later like that's what's actually going on it's like people build MCP servers for themselves I probably don't even know 90 % of the MCP servers that are anthropic because you know they might be in research and I might not even see them or I just don't know because people build for themselves but do they host it themselves is there a remote they effectively have a command to launch it and it just launches in like a Kubernetes cluster for them so it's like actually managed.

29:05Yeah, that's good infra for anyone at a large company to build. Any platform infra. There are platforms that offer that to you. For us from a security perspective, we want to build these ourselves. Yeah. But they're like the person who built Fast MCP, Jeremiah like a company that offers like Fast MCP Cloud, which is a little bit like that. You just like two commands and you have a running instance of an MCP server that talks stream of HTTP and then a lot of enterprises use things like LightLLM as a gateway and then they can even do like just launch standard IO servers, attach them to the gateway and the gateway does all the authentication, all the hard parts of MCP for them.

29:44And so there's a lot of ways to do this, but that's good infrastructure you really want to have is just like make it trivial, make it like one command to just launch an MCP server that was a standard IO server and suddenly it's a stream of HTTP server with authentication integrated and you as a developer only had to do the standard a part yeah i love calling that stuff out because people will take that and actually put this into their companies so um yeah otherwise also the alternative is chaos reinventing everything uh shout out to jeremiah actually i did invite him to do a workshop on fast mcp yeah at uh my new york summit yeah he recently a very great blog post about like a lot of the usage of mcp you're actually seeing is internal in companies.

30:26And that's actually what we see at the moment too. It's really cool. Like in what companies? Internally in companies. In big enterprises, you see MCP everywhere. And it's actually way growing way faster than you would think because it's mostly internal to companies and we are people seeing it. About discovery. So you launched a registry. There were registry companies. There were gateway companies. The official registry now has other registries putting their own MCP in your official registry. We need more registries, man. Just one more, bro, one more. Yeah, what's the... A registry to rule them all.

31:01Any learning from that? Like launching a registry for like a new technology and like whether or not, you know, people... Like, you know, Smithery is one example, right? If you go on the official registers, like all these Smithery AI MCPs that you need to authenticate through them. So it's kind of like just a pass-through registry in a way. How do you see, how is this going to shake out? I think we saw a lot of these like different registries come up and we really felt that there is a need for basically like an NPM, PyPy kind of approach to this, where there's one more central entity that is where everybody can publish an MCP server to.

31:35And that's really where the original registry came from. And we really wanted to make sure that at least we're encouraging the ecosystem to have a common standard of what these registries can talk to. Because what we want to do, we want to live in a world where a model can auto-select an MCP server from a registry, install it, and then all the given tasks that you have at hand, and then you just use it, right? It should kind of feel magic. But for that, you need like some form of standardized interface. And so we've got to do, and that was really the inflection point of like, we started quite early working with the GitHub folks, even in April.

32:09And then I got distracted with other things like authentication and work on that. And so what I want to see, and I think where we are slowly, but this is slowly heading, is a world where we have the official registry where everybody can put their MCP server, but this is the equivalent to an NPM, which has the exact same problems of an NPM. Like everybody can put it there. Basically, you don't know what to trust and what not to trust. You have supply chain attacks. These are just fundamental properties of public registries. I mean, that's why we have this concept of sub-registries, which then like the smitheries and others hopefully can do, where they can filter and curate on top of it.

32:47And that's really the world we want to live in. I don't think we're quite there yet, but we're slowly getting there. like the github registry is is curated after or speaks the same format as the as the official registry and so what we want is like you as an as a company uh can have an internal registry that is a curated form of the the official one plus maybe you own ones i mean that's the one you trust and it speaks the same api than the official one and if you have like a vs code or anything else that wants to talk to a registry you just connect it to yours and you're you're good to go and that's that's really what we want to do it's interesting because npm in a way it's almost like a download gateway you know it's like i'm not really using npm for discovery that often i don't go to npm and search for packages it's kind of like i find them in other ways and um is the cdn yeah yeah i'm interested if you see like discovery is like a core piece of like the registry or like if you still assume that like there's going to be some other way that the hn discovers.

33:46I do think discovery is important in the model world, but I think that's where it's different from MPM because we're building something for AI first and we can assume there's an intelligent model that knows what it wants. I think that's something that didn't exist before, right? If you, maybe, I don't know, if you would build modern package management systems with models at heart, maybe you would do a similar approach of just like, here's what I want to build, just figure out I don't care what packages just install, just do it, right? I mean, that's the equivalent in the end of the day. But again, with the public registry, you should probably not do this because it's a dumping run for everybody.

34:23You want to do it against the curated, trusted registry. I like your phrasing that the model knows what it wants. Yeah. Because I think there's a lot of, there's a dream that agents can use the MCP directories to discover new servers, install it for itself. That seems like very AGI if it works. Yes. But it may not work. And I wonder what needs to happen in order to do that. I do think we need like a good registry interface on one hand. And then the second part is just like, we need to build for this and see how it works and what does. We need like trust levels, maybe. You definitely need trust levels.

34:57You need trust levels. You might need some form of like, yeah, you need trust levels. You might need some form of signatures, for example. Like one of the ideas, I'm not sure if you're going to do it. It's just a random idea. But one of the ideas I always had is like, you can attach like signatures from like different model providers that have scammed this MTP server and say, we trust this. Here's the signature from Anthropic that these tool descriptions are safe. And here's the like the signature from OpenAI that these are trusted by us. And then you can decide. Oh, wow. So I think these distributed code signing.

35:29It may be. And it's not just really distributed, it's just like central in a way, right? But I think this is the kind of stuff you will require. or, but I think in the simplest form, what you can do, where you probably see it first, is in scenarios like internally to a company where you have inherent trust because they will use a private registry. They're effectively using private registries already for NPM, they're using it for PyPy, and they will also do it for MCP servers. In there, you have implicit trust and then you can just search. Yeah, right. And I think that's really the interesting ground where we want to experiment.

36:04And that's like, we have our internal registry in an effective way because when you launch via John's infrastructure, like an MCP7 that gets registered, right? And so we need to go and experiment with that too. Okay. I actually wanted to also ask, you started running some events over in London. Yeah. You had the Agents Hackathon and you had Dev Summit that you called out in your timeline. Yeah. I just wanted to get anecdotal stories of stuff you learned as you saw the community spring to life. So we had two big summits this year at the MCP Dev Summit in San Francisco. And the one in London too.

36:41And the one in London. And I think what you learn is a few things. I think that the one thing is that you, that's very hard to get. Otherwise it's just like these stories around how people use it internally in their companies. And there you see some of the struggles, but you see also some of the success stories. and one of the interesting bits that which I really loved is like particularly London you had a lot of financial people there because it's like really a financial hub and it was actually the whole conference was in the financial district and learning just like the kind of problems of like things you need to enforce because you have legal contracts because like financial like regulations these were things that were that I did not know before and I learned a lot about like okay what does like a thing like an MCP, like a communication layer need to look like if you have these constraints that in a normal development world doesn't exist.

37:37I'll give you an example. If you are in financial services and you're exposing some data, that data might be coming from a third party. And you must guarantee that you attribute that third party. And it's a legal contract. You must, if the client has placed this data to you, it must tell you this came from this third party. right and these are constraints that just like in the normal model world don't really exist right but like in the financial industry this is like legally enforced and so these are the things you like okay how will how will this work in a world where i'm saying we're for mcp and so now that's when we like started like creating this financial services interest group that bloomberg is heading up um to like figure out like what are some of the things that you like a client must do if it wants to speak to our financial services, MCP server, for example, and, you know, what are the things that need to be respected?

38:30And I think that's the kind of things you only learn on the ground, in the conferences, talking to people, right? So I think there was some of these learnings there. I think the other things that you just see is like just how many people are building and just the excitement and like the creativity that some people bring to this, like that I just love, right? Like, and from areas you didn't expect, right? Like I love the guys at Turkish Airlines who just built like the Turkish Airlines MCP server you can search for flights and stuff like that. So that was always fun. I love when like people bring some really creative parts to the MCP ecosystem.

39:01So I love these communities when they come together because you're just meeting things that are a little bit outside of your bubble and you just get some input. And I think there's a lot of learning there. And so we're going to repeat it again. We're going to do it in New York in April, I think, or March or something like that. And then we're going to do it again six months later. And I absolutely love that. Any good sampling use cases that you found? Not so much. Okay, yeah. That's always the, you know, last time we talked about this. We should use it more. You fix sampling a little bit, man.

39:28Like we, I think one thing I learned from sampling, like everyone wants to use tools with sampling in tools that are not exposed via the MCP server. Like when you want to do something, you want to have a set of new tools that you only want to use during that sample call. And we just had no ability to do it. And then we just fixed it in this iteration. And so we hope to see a little bit more, bit of more sampling use cases. You will find every now and then an MCP server that does it. But particularly as MCP servers have moved away from more local to be more remote. In remote cases, it's probably always better for you to bring an SDK because you have full control, you can deploy it, you can deploy an API case and maybe even charge someone.

40:07In a local case where something is really powerful because you're shipping something to a lot of people and you don't know what is their, what is the model that they have configured, what is the application they plug it in. It might be VS Code, it might be Cloud Desktop, right? And in those cases, sampling is useful. but also like clients just don't support it. So sometimes it's one of these things I'm like, I'm still sad about it. I still think it's a very powerful idea. But you know, you got to win some, you got to lose some, you know. No, no, no. You're also, you know, upgrading it. And, you know.

40:35My hopes are still up there. Yeah, yeah, yeah. Like my, in some ways, you know, when you get it right, this will be the real agent-to-agent protocol. Yes, yes. Are most of the use cases that you see still data consumption? That's been my use case for MCP mostly. Yeah, it's context engineering. Getting data. Well, the most action MNCP takes is like update the linear task status. Have you seen very complex like MCP taking action workflows or are still people mostly using it for context? Most people use it for context. I think that's a vast majority of usage. It is in the name, model context. Yeah, yeah.

41:11And Nick Cooper from OpenAI always keeps telling me, rightfully so, that the name MCP was probably a little bit poorly chosen. because it feels it restricts it a little bit, which I agree with. It's mostly data use cases. I've seen people doing deep research via it. I think people expose agents via it, and so they are a little bit more complex, but it's not super common. It's what people have experimented with. They have the deep research use case, I think it's a good one. That's not too uncommon, where people do custom research for it. But beyond that, yeah, most of it is really data. Beyond data and deep research aspects, now you have also this new aspect where people expose like UI components or MCPUI or what we're going to call MCPI in the future.

42:03And I think that's super, super promising. And I think that's really quite fun. That's actually you see a lot now with ChatGPT apps, with MCPUI in general, that you see a lot. Yeah, and you have the tasks in the last... In the tasks. Yeah, well, I mean, I'm curious because like if most use cases are like context and then you build tasks, it's almost like people are not really using it for tasks. So I'm curious like how you design it, like what you expect people to use. We design tasks because people come to us and go like, okay, we really want long running operation, which is basically agents.

42:33We want like a long, deep, deep research task that finishes in an hour. We want tasks that like might not finish within a day, right? And people have like awkwardly tried to do this with your tools and you can. Because tools are effectively just an RPC interface at the end of the day, but it gets very quickly awkward because now the model needs to understand, oh, I need to pull this. And it's just not very fun. It's just not a first-class primitive. And you run into a lot of limitations. But it's come from the fact that people want to have a long-running agent. And that's something we heard from so many areas and people trying to do this, that we really felt we needed to do something like a task.

43:12Like on GitHub issues from big companies, everybody was like we need something that long running operations is really top of mind so I really think now we're going to see a lot of it but it's a little bit early to see how good it's going to go because it just landed in the S &P case and it needs to land in the clients and then we're going to see more of it but I think you will see a lot of the custom deep research parts in others Yeah, I'm very bullish on tasks I think it was very important to get right basically every orchestration or protocol needs has a sync version and an async version yeah exactly has an async version any like design choices that you want to call out that you know there were two directions and you picked one in just the overall design of tasks yeah in design there was a lot of conversations like some somewhere like okay is this just asynchronous tools do we do a different primitives in the end of the day it was important for me my litmus test for it was always it needs to be able to like Like if I want to expose something like Cloud Code or like any other like coding agent as an MCP server, hypothetically, this needs to work.

44:19And a pure asynchronous tool call would just not do this. You want some form of operation that can return, for example, intermediate results in the long term. You want like, okay, I got to this result by calling this tool, this tool, this tool. I had this other input. I had this other tool. I did this. And now this is the result, right? That's really what you want to expose. and task is early and it doesn't do that just yet but it's built in a way that it will be generic enough to be able to support this. That was the main constraint. The other constraint was making sure it is it's it's not a copy of tools where you can think about like okay we just do tools again have slightly different semantics but instead what it's doing is like just like you can create a task by calling a tool with a certain set of metadata fields.

45:14And then it automatically creates a task. So the task itself is just the concept of a container that can do something asynchronously. You do something asynchronously from starting here into ending here. And the thing we're doing is a tool call. I mean, that opens the door to later plug in other things and maybe even other tasks. Like observability as well. Yeah, potentially. Which is obviously going to be important. So I think that was really the design goal, which makes it a little bit more abstract, a little bit more complicated to implement, but that goes away because the SDKs just do it for you.

45:43And the SDK, in the end of the day, you just go like, async call this, and you return something. I mean, there you start to overlap with other async, like trpc in JavaScript land, or whatever Go, Protobuf stuff that Go people have. In the end of the day, it's designed like a classic operating system, interface, like you create a task, you pull it until it's done. And then you can make an optimization, which we're going to do in the next round, which we didn't get around. It's like, okay, instead of having to pull every minute or hour or whatever interval you choose, the server can call us events, call you like a webhook or something and go like, I'm done, right?

46:27That's the optimization. But the actual core interface is always that the client can pull. And that's actually how like operating file system operations and an operating system can work is like you pull, it has the file changed has the file changed but you can also use like a modern interface on the kernel like iNotify or something like that or uRing or something like that to tell you oh I'm done great the file has changed there's a trick I learned where like servers can hold the HTTP connection until it's done and then they terminate and that's the signal to the callback which we do not necessarily want to do because it might take a few days and I don't know how people it's very irresponsible but it's cool yeah yeah yeah there are plenty of ways I think we were just going to go the webhook way, honestly.

47:09Tasks are really interesting. And we basically have to invent this when we did this at the Devon API, Cognition. And I think that's also like an interesting reinvention of like, well, everyone is going to need some kind of long-running operation. And this is, well, when you're calling an agent, you also need this. Yeah. But the interesting part for us is what MCP is always trying to do. MCP always tries to encapsulate what currently people are trying to do. And we not want to be prescriptive what you're supposed to do in a year from now. We don't know. We don't predict. We did tasks because people are like, we need this now, right?

47:44We needed this basically six months ago. And we're like, okay, I guess now it's time to do this, right? Instead of trying to do, being predictive of the future, which is why we're trying to keep the protocol somewhat minimal and have, I think to some degree, achieve this, although other people would think already there's too many primitives in the protocol. One minor thing, and so let's say super long-running pass. lots of messages go back and forth. Anthropic actually was a kind of leader in context compression and compaction maybe, let's just call it. And I think a lot of the other labs are also doing the same thing.

48:17Is there a way to handle that or do we just statelessly sort of cut context and it's fine? Do you need a full log of everything that happens? Or no, you just ask the phone. Yeah, right? No, you don't. I think they're, this is the thing, right? We're very early in the industry still. We're learning a lot about like what does the model need, what does not need, right? And even today, like some agents start to like drop two call results after a few rounds because they don't need it anymore. And I think that's very, very, very good. And so I think besides compaction, you will see just better mechanics of like understanding what you need and what you don't need.

48:55Like for a long asynchronous test, you might have a way where like, okay, maybe for a while the model sees it, but once you get the result, you just drop everything else. or you might even call like a small model, like a haiku model and go like, what all this I should retain, tell me, right? You might be like the AGI-pilled approach would be just like, let the model figure out what it needs to retain, right? And so you can see both worlds in them. And I think there's just lots to learn. I think there's not the one answer yet because I think we're still figuring these type of things out and we're just improving.

49:25And compaction is a good step for it, but I don't think it's the last step there either. It's actually the most obvious one, but I don't think it's like, I think if you pay more attention to it, if you particularly think about like, okay, what could you train a model to do here? I think we get to much better ways of doing that, but they're all like independent from how you obtain the context. And I think MCPI always see is like back to like it's an application layer protocol. That's just how you obtain the context, how you select the context. That's the problem for the application. And that's the problem all the agent applications will have at the end of the day.

49:58and there will be a lot of different techniques. A year ago, everybody would have told you it's RAG style stuff, but it's now apparently dead, right? And now we do use models, we use compaction. So I don't know what's going to happen in a year from now. Cool. Around MCPs, another question I had is like, how do you see them as being used by developers to build AI apps versus being a protocol for AI consumers to plug things in? I think that's one of the main things people get wrong where it's like, well, I can just use a REST API. Why do I need MCP? And to me, it's almost like it's not really for the developers to use.

50:31It's for like people using AI tools to just plug things in. I get the comparison with the REST APIs quite a lot. And I think it's funny enough because there's two problems in general. Like the first one is REST does not tell you what to do on authentication. The second part is that really complains to me about like tool bloat. Have you looked at like the average open API spec lengths? If you put that into a model, like you will have a lot of bloat there too, right? Actually way worse. and funny enough when people try to like map one-to-one things often the model gets slightly confused because you have like search by name, search by ID, search by something, right?

51:05And like suddenly you have like five tools that look very similar to each other and the model goes like, which one do you want, right? I have no clue anymore. So anyway, that side note to REST versus MCP. But I do think MCP, I want to live in a world where it's like very much like a consumer-focused thing but something consumers should know about. For them, what I want is, I want a world where you go to your application, you say, do this, and it should just do the thing. And it should just connect with the right services that MCP is under the hood, is a detail, or that the developer needed to know about.

51:41Because that's the communication channel that they're talking. But in the end of the day, you just get your tasks done, right? And I actually prefer a world where nobody of, like my mom should not know what MCP is, right? If she wants to use cloud at the end of the day. But I do think it's very focused on that pluggability of like an external like service. And in that regard, more like on the consumer focus side. And there are still use cases for developers in general, like first of all, as builders, but also like I still love my Playwright MCP server, man. Yeah. Well, I thought Chrome developer tool, the new Chrome one is like the new meta.

52:18I also understand like for developers right like that run like cloud code locally you know like things like PLIs can be better approved right to some degree and that's okay. I'm curious about the MCP apps UI with what you're talking about where it's like every client like ChatGPT has their own right? So it's like if I'm used to the MCP app of this product but then if I go in ChatGPT there's like a different version that they curated it's kind of like a different experience so I'm curious how you feel about that especially now that you have OpenAI and the foundation do you feel like all of this will be MCP backed in the same structure there's two influences MCP UI existed as a project which had a lot of really good ideas OpenAI took some of them and really improved upon them and now one thing we just announced three weeks ago on the MCP blog is that we're actually working with all two of them together to build a common standard and so we're really hoping that we're getting back to the world where you build for one platform and you can use it across all of them.

53:21You build for chat GPT and you might be able to use it in Cloud or in the Goose or whatever it might be that the program of your choice that implements this. But I think the general problem is what we have is I think that there are certain problems like if you think about a modern AI application, everything is very text-based and that's okay it's nice but there's things that But as a human, you're just way better suited to do it in visual, right? The most basic example is like you want to like book a flight. Seat selection, right? Like you now get select. Like you want to do seat selection in text?

53:56It's like here's like the 25 seats you have available. Like nobody fucking wants to do that, right? Like I have no clue where these seats are even. That sheet-based drawing. I don't know if you want an application that you can select with or it might be like a theater that you want to book for or something like that. it's so obvious that you do want to have some form of like an application in the user interface that the model can navigate and the model can interact with but you as a human can also interact at the same time and i think that's what we're looking for and so i think it's just this next situation of like building richer interfaces because the pure text interface is just somewhat limited and there's very natural things and you like you see this in music production you will see it of course or you will have like certain brands that will deeply care about presenting their interface.

54:40Shopping is a good example, man. Shopping has like 20 years of A-B testing, what's the best way to sell you something, right? And shopping interfaces are super complicated, actually. And you just want a way for displaying that to the user so that it's familiar to them and that they can interact with it. And that's what MCP apps is in the end of the day. Technical direction-wise, is the iframe the way they were? Yeah, it's an iframe. You are serving basically raw HTML over an MCP resource. It goes into an iframe and then it talks to the outside rear post messages over a specific interface. And so what you can do now, you can, because it's raw HTML and you're not really loading some external content, you can analyze it in advance if you wanted to with security.

55:28And because you have an iframe, you can, the external application can just speak like a very clear, security-bounded... Yeah, and this has been in browsers forever. I think the I'm scared of it only because I hate cores issues and iFrames always have cores issues yeah but this again this does not load anything external like it should not right like there probably are restrictions that we like then iterate and iterate and then in five years maybe it has like 25 cores headers and whatnot whatever right but but I think we're starting small again it was like pure raw HTML you should probably not have external references so you don't run into these issues but you're right and can I inherit styles you know I think you need to put it in mine you will want it I feel like this is really minor but UI people care about this it should look like chatgbt me and try to chatgbt should like cloud I think that's a very good question I 100 % agree with you like brands and others who deeply deeply care designers 100 % and that's something we need to figure out and that's where you need to get it out of the door and see how people use it and then iterate on it.

56:40That's why I don't think it should be an iframe long-term. I don't know what the solution is. Okay. But we need a new iframe that lets some permeability because of this stuff. I think that's sensible, yes. Well, I don't know. But the other solution to the problem is the IGI build approach of just give it a tool that says, give me a style sheet. And the model can call you and tell you what you're supposed to look like. Okay. Should an MCP app know what it's being used, what the parent application is. You know what I mean? It might be. The application also exposes tools, right? The model is free to call it.

57:16Right, right, right. Okay, so maybe standard as an interface for people to pass down styles. Maybe, yeah. I don't know, but it's a very good question. Let me ask the team. I'm just like, I'm mostly like directly there. I'm like not in the weeds of doing everything there. Yeah, it seems like a little bit of a surprise to me. I never really paid any attention to MCPUI. and then suddenly you guys all adopted it. I was like, okay, well, I guess this is a part of MCP now. And it went from a purely backend concern to now frontend. It's also like Notable is technically an extension to MCP. Like it's not MCP, MCP.

57:49That's a pure technicality because... It's a governance thing, right? Yeah, it's mostly like if you are a client that can render HTML, then you might want to consider implementing it, but you're still an MCP client if you don't. And the reality is, it's like your average like CLI agent can't do it, right? So they will never do it. And so I think that's fine. Are there any other extensions that are similar? We're going to look into like financial services as an extension. We're like, okay, you might, you might end up in a world really a year from now. There might be clients that have like certifications that they are an Amp, like, and get like a signature that they are like financial services MCP clients.

58:27And they can prove it for the server. and only then the server allows connections because it knows they're respecting attributions, these daily contracts that you put into place. And you will see this everywhere. You will, if you want to deal in the long run with public servers and public clients that do like deal with HIPAA data, like healthcare data, you will have to have guarantees. Isn't it part of just auth or auth? Not necessarily. Like I give you an example. Like if I have, the client might need to have five servers installed and if there's one healthcare server, that healthcare server might tell you you are not allowed in this session to use any of the other MCP servers because this data I'm giving you cannot leave you, right?

59:10You must guarantee that this data doesn't go anywhere else because it's HIPAA data, because it's financial data, whatever it might be. This is a good example and that might be some of the enforcements you need to do. because you just like, you don't want to have your or social security number or healthcare data show up in the near of accident, right? Awesome. We're going to transition and have the rest of the AAIF group join, but any final call to action, like either, you know, people that should join your team, people that should contribute to the MCP spec or anything else? I think the most important part is still building with MCP on a day-to-day basis for people to just go out, build really good MCP servers.

59:50I think we see a lot of mediocre MCP servers and some very, very good ones. And just building good MCP servers, looking at how to use them. I think that's super important. The second aspect to that is we're a fairly open community and we're running it as a traditional open source project that is based purely on what people are able to put in in terms of effort and time. And so just being an active part, either giving us feedback, being in the Discord channel, talking with us, giving us ideas, while also just helping us implementing like the TypeScript SDKs, the Python SDKs. We're always looking for new SDKs, right?

1:00:25Like we have ActiveGo SDK development, but like we don't have a Haskell SDK. I don't know if you're a Haskell developer, maybe you want to write that, right? Yeah, there you go. And so I think there's a bunch of stuff we can do and be part of it. And I think, yeah, don't understand how much you can just be part of the community, but also just like go and build. And I think there's so much opportunity now, particularly to build like amazing clients now that we have understood progressive discovery better. now do we have understood code mode better there's just this next iteration of clients to build and the next iteration of servers to build that I'm just looking forward for people to do yeah my last question or call out is I wanted people to hear directly from you I sense the energy I'm very excited by everything that you're doing but a lot of people are anxious about joining MCP joining the Linux Foundation they're like oh is this Enthopic taking his eye off the ball can you address those concerns yeah I love that you asked me that like i think yeah yeah i can totally see why people think that but like it's actually quite the opposite like the commitment of anthropic is the same right i'm still we still have the same people i'm helping with the sdks we're still super committed in our products to mcp i'm still the core maintainer nothing has actually changed what really is the main part of the foundation is like two things the number one is like making sure that the whole industry knows that this will stay forever open that this cannot be taken away and there have been there have been like i probably would never do this, I think, but there have been histories of companies going like taking an open source project and suddenly making it proprietary again.

1:01:55We have protocols that are proprietary. Look at HDMI. Look at like what's the problems of HDMI and Linux. Wait, what's on HDMI? HDMI 2.1. The HDMI forum does not want to allow AMD to develop open source Linux drivers for HDMI 2.1. Really? There's some. Look it up. Wow. So, you know, there's people like keep a very close tap on it and what this does is like no this is now owned by a neutral entity it will always stay open you can use the the word mcp nobody's going to sue you over it so there's a bunch of that just giving the ecosystem and the industry that confidence that this stays neutral i think that's important the second part to that is that i think one thing i'm if anything i'm the most proud of is that i think we have set the the tone for open standards in the industry and being able to now use that momentum to build like a community and a space where people can come and bring really well done, well supported, well maintained projects and have them part of this foundation.

1:03:04I think that's the that's the other part to that. But the funny part is like our bar for the foundation is going to be like it needs to be like really well maintained. It's not like you're getting you're taking the ball off. It's actually exactly that what we don't want. And so we will not do that for us. MCP is still core to the product and still super important, philanthropic. And so we're still just as much as committed as we've ever been. Amazing. Awesome. Thanks for joining, David. And we're here in the studio with core team members of AAF. It's the biggest panel we've ever had on the podcast.

1:03:37So welcome, guys. Maybe we'll go left to right and introduce everyone. And also identify the voices for people listening on audio. I'll start. I'm Jim Zemlin. I'm the CEO of the Linux Foundation. I've been working there 22 years, and I was the person who helped facilitate the launch of the foundation, but take no credit for any of the technology work. That's to my left. I'm Nick Cooper from OpenAI. I've been there just over two years now, I think. I'm generally OpenAI's head of a lot of protocol things and very interested in the open ecosystem and our representative for AAIF, as well as a core contributor to NCP.

1:04:16Got it. What's another protocol that might fall under that umbrella? Agents ND, just in general, like not just the protocols, but also the product experiences of where OpenAI products intersect with other SaaS provider things and other systems. I'm David Soriapara. I am working at Anthropic, member of technical staff there. I'm the co-creator of NCP. and yeah, Anthropic can mostly lead all the MCP efforts. Great. And I'm Brad. I'm the principal engineer at Block. So by day, I build AI products and by night, I work on open source like Goose and the erasial author of Goose. It's great to see everybody come together.

1:04:55I think when I heard about the news, I didn't really expect it. It wasn't on my bingo card. So maybe let's have a little bit of inside baseball. So you obviously have open-end Anthropic and yesterday at the launch event, you were joking on how you didn't know that the two companies even talk to each other. And then, yeah, how did the conversation start? The conversation started out of two things. The first one is that on the MCP side, we always knew that we wanted to find a neutral home for MCP to make sure that the industry understands that this stays open, that this is something safe to adopt.

1:05:30And then very early in the process, as we were looking around, like, what to do about this, should this be a project in a foundation, should this be inside its own foundation which is like these common patterns you see for this kind of work and we got approached by our friends at Block to discuss because they were looking into like donating goose I think at the time and so there was a question around doing something together and then we approached OpenAI and they were very very welcoming and like very open to the idea as well and it slowly like formed and I think And, you know, at the time frame of this is like a few months, these things are not happening out of thin air in like a week or so.

1:06:12And so just a lot of conversation, like what do we want to do? What are the kind of like constraints we want to have? And what is the thing we want to build? And of course, we were looking for where to put this kind of stuff. And that's where the Linux Foundation comes in as, I think, the biggest foundation of its kind. And certainly has like decades of experience helping companies through a process like this. and building what is technically called a directed fund within the Linux Foundation to build these kind of things out. I think David said basically all the story from my side as well, which is, so we saw this need to connect systems and then MCP gained such very large developer traction and we had OpenAI were very excited to use and then contribute and actively participate in this.

1:06:59And from my point of view, it was always very natural that this would grow into something bigger and move to a neutral place. And MCP has always been a foundation for communication between agents and contacts. In a similar way, the agentic foundation is, well, it's a foundation, but also it's the starting point where we really look forward to other contributions, like starting with Goose, our own agents MD, where we're really open for a lot of technical contributions to build out a full agentic ecosystem. I'm curious, Jim, I've been to Linux Foundation events before I was plugging them. it's almost like it's an MCP so early that like how do you even structure it in a way?

1:07:38I'm curious because so many of the technologies that the foundation supports are kind of like core pillars of infrastructure and the internet. This is probably like the youngest technology that you brought in as a foundation. What are the goals of it? Yeah, I mean, I think what's interesting here is even though it's young, I think if you, I think AI years are kind of like dog years. Absolutely. do you use this metaphor but yeah totally this is why i run three conferences a year yeah exactly you can't do annual i think last night someone was asking what do you what do you see a year from now and i'm like well if i dial the clock back a year would have i anticipated where we're at right now there's no way and so i think part of the thing with mcp is that we're just living in this kind of dog years velocity uh in the past i think things took a lot more time to coalesce And what is clear is that a lot of people are adopting MCP.

1:08:35You see it in commercial products that companies are rolling out. You see a lot of usage in the enterprise already. And there still is a ways to go in terms of the technology becoming mature. I think the same thing held in internet protocols, you know, that took a little bit longer to mature and the internet matured over time. But I think the thing I'm most excited about, it's becoming clear that MCP will be a key protocol for this technology movement. and I think you know David and these folks were all pretty wise to realize that you know if internet protocols had been owned by a single entity he'd still be calling it American online America online it like you know it would be it wouldn't work and uh I think that this has got all of the underpinnings to be a huge movement and at the Linux Foundation we ask three questions for every project.

1:09:31Will this be meaningful and impactful for industry and society? The second question is, do you need more than one organization to collaborate to do it? Otherwise, you don't need us. In this case, clearly we've got that. And three, can we get the resources and build an ecosystem around it? And 50 companies on day one, you know, a huge set of folks in line to participate and join my email inbox. I'm sure your guys are too. like full in 24 hours how do i participate we want to contribute how do i get in there i've never seen that kind of inbound interest starting any project at the lynx foundation in 22 years how do you pick so you got all these people reaching out you know there's good and mad it's a really good question i think it's like how to pick uh how we expand the foundation itself from a governance standpoint, but also like technical contributions and how can the foundation best support them as well.

1:10:30That's like really tough on my mind. It's like the first thing we need to like define some structure and work out what we, like how to bring it all together. But I think even before like those details, there's such value in establishing this one forum that people can come to. Like even having a list of eager technical participants and potential opportunities, that's a huge opportunity in front of us to like distill what's truly meaningful to developers users and everyone and very appreciate the links foundation reacting as like sort of a galvanizing rod for this like attention. Brad, on the sort of block and goose side it's an interesting the involvement that you guys have had in the sort of engagement that you guys have had what was your calculus in joining the AIF?

1:11:15So for us I think it's like in developing something like Goose I think the thing that I see it as being part of this umbrella is it's the most concrete piece. So you can actually like download Goose and use it in a way that you can download an AGS MD. Like what are those parts do together without having something that actually like connected to like a real client. And there's, I think, a lot of value in that because when you get into the protocol space, you want to add things to it, but you have to actually show like what it's enabling. Like, why are you making the protocol wider and putting it into like a reference implementation shows you like, oh, it's giving this value to people like very concretely.

1:11:59And I think there's some like, for example, there's like a spec for MCP, MCP apps that is brand new. And we've been working on MCPUI. For Goose? Yeah. So Goose has been like kind of a day one partner with the MCPUI team. Oh, I didn't know. And so now we've had NCP apps, we'll go, we have opened an issue today about how we're going to go get that into Goose. And so that's something where I'm people, I think you hear something abstract like that. Like what is send it? What is the server sending an iframe to the client like do? And I think Goose is a place where you can see it like, okay, you're going to build a dashboard or you're going to have this enhanced chat experience.

1:12:33And so this is something where I think we collaborate more and more to say like, this is what it looks like and how you look at some of these abstract things and make them real. I think the other tidbit here maybe like back to the history of both MCP and Goose is like Goose was the first open source agent interface or agent that reached out to us and worked with us to integrate MCP and I think Rad is actually like technically the first non-anthropic contributor to MCP ever on like day two or something like that like very very early so this goes all the way back to like November last year to like the partnership of having MCP inside Goose.

1:13:11Yeah, we had a version of Goose that was still, you can go check the GitHub history. It was there a little bit before MCP came out and we were sitting there with like a plugin ecosystem who were like, this is awful. Like, why would anyone come develop a plugin just for Goose? But we saw all these opportunities and so we started talking to Anthropic and we were like, I think that there's a space here for a protocol. and they're like, well, let me tell you about and it was really cool to see, you know, what the Zets site. No, no, no, we didn't. We reached out before we heard the Zet thing and so we were like, okay, like, yes, we just want to, like, we want to pile onto something that has a chance of succeeding because as, like, a client it's like an ecosystem, right?

1:13:55Like, the more people are here using it, you get more value as a client than as a server because, you know, your servers are going to work with any client and then as a client, you know, you have this giant library of servers and so that's been like a big part of what Goofs does is that it's not really like it is a coding tool. People use it as a coding tool, but you can turn off the code part and you can just connect to any MCP server. And so it can be like operating like, you know, a science experiment. I've seen that or like just like Google Docs or whatever. And I think that it kind of shows you how MCP goes beyond just like the bytecoding space.

1:14:27Yeah, I think as well. It's also the fact that it's concrete is so important. Like for all these standards, like there's a long history of standards throughout computing that like people like proactively write a standard and then when you know the it's actually tried out it has problems yeah but like for mcp and like all these new agentic standards we're coming with we really want demonstrated utility like what the most common thing on the core committee is like there's a proposal and we come back to people saying like have you tried it out does it work The protocol is about communication. So if you're trying something out, you need collaborators, and you need concrete open source projects like Goose, and you need clients, you need a variety of servers, because it's only with that sort of open ecosystem that you can meaningfully understand if this is actually going to work.

1:15:17I totally agree with that. I mean, I think the world of standards and open source development are just merging, right? You sort of co-develop these things together. I think I was trying to figure out whether David is VentSurf or Linus Torvalds for agents. And I think maybe it's a little more, it leans a little more VentSurf and then maybe Ghost is a little more Apache web server and my whole Linus part kind of falls apart at that point. But you do need something substantive to try the protocols out in order to make sure you know how to improve them. It's that feedback loop that's so critical. OpenAI also has a coding agent that is open source.

1:15:59I think what's the thinking there apart from like, well, would Codex ever be donated to AIF? Or we just don't know yet. I think the short answer is we don't know yet. But like, it's sort of like a feedback loop, which is in this open ecosystem, like we don't want to have too much alignment all on like one implementation, one thing. there's like real value to users and developers or whoever's the participant to like active competition in some parts so there's this balance of like we need openness to foster like collaboration and experimentation but like i would like to see a variety of coding agents and each one might deliver unique value different value and be free to explore independently so it is sort of like a careful balance here there's a bit of like a taste making approach to like contribute things that benefit from being open.

1:16:54Like AgentsMD is an example, which is open up any GitHub repository, it has this file, it works the same way. Like if everyone sort of did their own thing there, that's very low value, potentially damaging in a way. But so there's commonality value, whereas for actual concrete implementations and projects, it's great to have reference implementations in many ways or experimental grounds like Goose, but I really favor a huge variety of them because that way we'll see what comes to be the best. Is there a roadmap for what you want to add? For example, the Agenda Commerce Protocol, like ChatGPT already uses, but that's not a part of it.

1:17:32There's no model as a part of the foundation. Do you already have a roadmap? Or like you said, you're just kind of like going month by month and what are people using and what should be in there? I think we don't have a roadmap in the sense of like, well, projects lined up. But I think what we have is principles by which we will select products to some degree. And I think the effort here is mostly around sitting together after the foundation is created and then evolving these principles as we're seeing people going to ask us about the projects they would want to put in. And then develop the foundation further as time goes.

1:18:12But at the moment, I think the most important part is that we have the principles in place than go and having the conversations with people who want to be part of this foundation. One principle that really comes to mind to me is composability. I often use the analogy of Lego blocks sort of thing, which is agentic systems are a sum of many, many parks. And so something that I hope the foundation can evolve to do is have these interoperable, composable bits that all work together, pinkly. and so we don't have a roadmap of like future contributions but like i welcome all contributions that play nice with other contributions and like really create this potentially like a future flexible open agentic stack to be like not a universal agent but an agent that suits everyone's purpose or need yeah it's tricky you got it's a hard and these guys have the harder job of early in innovation cycle, you don't want to restrict innovation by saying like, oh, well, this is the one versus that one.

1:19:17But you also don't want to let every single random thing into an organization like this. And so I do think you need this, tastemaking is a good way to describe it where a group of elite architects and developers, folks like the three people sitting next to me are more curating. And, you know, some things can work, some things might not, but there needs to be a process which I think will define to do that curation that happens via tastemakers. And it's more of a, not just more, but essentially a technical effort, not something where a committee of, you know, folks from vendors get together and say, well, my product should be in this roadmap and that guy's product should be in this roadmap.

1:20:07It tends to not be very successful. Which leads to this other principle that we really want projects that have a little traction, that are well-maintained, that are very, very healthy in the plantation. I think that's super important to us. Right. I think you're looking for something to have already found a niche and to be established because you don't really want to be pushing a speculative architecture. You really want to be embracing something that already works. and so I think a lot of the stuff that we're talking about like payments or like kind of I really enjoy the like interface to model architectures I think those are really interesting but it's not yet obvious that that pattern needs to exist and so that's something where we can go see it and like try to make it work in some projects and then can bring that back if it really has a role.

1:20:58And on the opposite, what's my incentive to bring my project to? I have a a project with adoption is well maintained it's healthy what's the benefit that i get from donating to the foundation i mean i can start that but i'd love to hear from these guys as well i think what you all technology is an implicit futures contract right and so you know if there's technology that has traction and uh that traction sort of wants to be built upon having that technology at a neutral place like the agentic ai foundation where the whole industry is making decisions about how to invest and when i mean when i say investment i don't mean like becoming a member of the foundation because you don't need to become a member to participate on the technical side it's decisions about hey i'm gonna you know assign 10 of my company's engineers to co-develop this with your organization, the contributing organization.

1:21:59And that's a way that we can all essentially co-develop together. And that will provide better support, more development velocity, higher code quality, because more people are participating in it. And that's a massive incentive if you want your technology to actually be used and adopted in industry and get more feedback and kind of a positive feedback loop of great project that gets great products in the market. That market feedback then allows companies to make money off of them. They then pay engineers to improve the project, better products, more profits, better project. And that's the incentive, which is a pretty high one.

1:22:42Could I add a technical sort of spin, which is none of these things are built in a vacuum. like all these projects build on lessons and learnings or practical code from other projects and that's a big opportunity like any technical technical contribution will bring its own unique value to the foundation at the same time it then gets to learn the lessons that all the other participants in the foundation do and like i found it really valuable over this past year working with david and others on the mcp committee about like it's actually that communication thing that makes our ideas more robust, makes the implementation better.

1:23:19We can be sure it's secure and safe and actually works. This requires communication. And that sort of, the foundation is the natural, like, town square, put this in a way. So one last angle on this. I think if you're working on a standard or a protocol, this is such an obvious decision, right? Like, the value in the protocol is about how many people are adopting it. So being a part of this, like, gets you that reach. But I will say, as someone who's working on a client and not a protocol, I think there's value there too we want this to be part of the foundation because we develop these ideas together to your point and so it makes it better we're donating Goose because we think it's going to make it a higher quality tool I actually have a follow up question on just the LF side LF has many other funds and organizations including Data and AI Foundation as well as dedicated PyTorch and all the other ones I guess why a new foundation?

1:24:14Well, because everyone's special. No, I think that the way we look at in this space, and I'll put aside the projects in semiconductor tech and operating systems and stuff, but in AI, we think of it sort of like how the market has evolved. It started with tools like PyTorch and the transformer tech that is used to create LLMs. The Linux Foundation kind of took a pass on a frontier model world because in the open source space, having connection to the internet and some intelligence and a computer, that's sort of entry. In the world of frontier LLMs, it's a computer connection to the internet, some intelligence, $2 billion worth of GPUs and a ton of data.

1:25:04Harder for consortiums to do that kind of work. So pass. Then you look at how, you know, reasoning models have come out, need to be, you know, in inference world, things need to be scalable. Okay, now you've got interesting technology, VLLM, Ray, things like that. They have to be deployed on something. Kubernetes is sort of that. These are all distinct components. Agents are a distinct enough set of technology that it merits its own community. Except for from data and AI. Yeah, because like a PyTorch dev isn't really doing a ton of stuff in agent land, right? You know, somebody working on dockling maybe is a little more adjacent, right?

1:25:46But not quite the same as somebody who's like working on transformer tech or VLLM. And so they are logical categories. I mean, sometimes stuff comes in over time and, you know, we sort things out later. We had early on in the telecommunications sector, you know, a software-defined networking effort, a network function virtualization orchestration effort, a whole bunch of stuff. All separate entities. And they, I was like, let's just bring all these things together because the technology is now mature. We're taking all this money in, but we don't really need the resources anymore because the market's already mature.

1:26:25and so it took me a year to get all these companies to decide to bring all these things together and not pay all these separate fees and have all these separate orgs i have a little folder in my inbox that says you know convincing people not to give me money but in this world i think it's a different kind of audience i think it's narrow enough i think it's specific enough to agents where it merits its own entity i think as well it um dovetails somewhat with the earlier thought like with the taste making aspect to this for these organizations to be effective they really need a focus like something that brings them together and ultimately like you can imagine an alternative where we snowball and there's only the linux foundation as this uber do everything remotely connected to a computer and that wouldn't be that effective so there's a taste making here as well which is going to be focused on the genetic systems and how they connect together and the GenderKI Foundation.

1:27:21But everything's about growth and evolution. So there's a possibility that later down the line, we recognize some natural affinity. There's something new, something old, and then they can be brought together. But the focus helps at the beginning, certainly. What's going to be the actionable outcomes? So obviously you have the funds to direct. I know a lot of the Linux Foundation does events. There's also eventually certification, things like that. what's the split of the foundation investments is a lot of it going back to different projects individually is it about the community building and then from people that have not been involved from the outside it's like this just seems like a nice blog post and a bunch of logos but like in reality how are things gonna be actioned yeah i mean 50 companies coming in to fund a bunch of blog posts seems like overkill right exactly um so i think there's a couple of things one the intellectual property assets now are owned by this entity.

1:28:18That entity is responsible for making sure that, you know, that IP is managed effectively, that licenses are complied with, that intellectual property problems are dealt with. Some funding goes to that. There's a leadership function where, you know, to help bring consensus across the industry and within developer communities, you have to have a special kind of someone to do that. And I think they need to be technically knowledgeable, but humble enough to know that the community is the one who makes the technical decisions. So kind of just sort of lead through influence to kind of help people organize things effectively.

1:28:57So you hire some people to do that. You hire people to do developer outreach, community engagement, because you want more developers coming into the community. So funding to go to that. And then there's a huge convening function. The Linux Foundation hosts 50 ,000 plus virtual meetings a year. So we have this like, I think we're probably like one of the largest users of Zoom. I know for sure we're the largest Slack user in the world. And so that convening function is critically important. Make it as seamless and easy as possible to convene. And then, yeah, we hold events because I think, you know, to your point, developer engagement, face-to-face, being the town square where you physically get together means something.

1:29:46So I think you guys have been to KubeCon. You know, we have easily 10 ,000 people that come to that conference twice a year. in europe this summer there were 13 000 folks there who you know come in and they exchange ideas the core maintainers get together and make real decisions and then the last thing we spend resources on and you can go even just check these out for some of our other projects is we have a whole platform that enables you know maintainers to look at their community and understand you know like what's our velocity? How many developers are we adding? Like what's the social media scuttlebutt around this project?

1:30:25What are leading indicators of adoption? How's our security doing? Like, you know, do we have good practices about application security? And those are all things that we, you know, invest in to help make these communities, you know, better commercially adopted so that we get that positive feedback loop of like adoption that gets more investment in the of developers providing input, and that virtuous cycle kicks off. That's where the funding goes for these kind of things. I put in that question into our doc because it says it's a directed fund. So my cheeky question was, well, what are you directing them to?

1:31:02So directed fund gets into the nerdiness of this. But the reason we structure it that way is somebody has to own everything. The Linux Foundation is actually the ownership vehicle. And remember, we separate technical governance from the governance of actually how money gets spent because we don't want this sort of pay-to-play aspect of technology that tends to screw everything up. And so the directed fund is really like, you know, real stakeholders who really care about this tech, put money in and use it in a way to help build the market and the community and all the things I just talked about and just let developers do what they're super good at, get together, solve tough problems, be, you know, tastemakers.

1:31:48That's something that we separate. Yeah, I think there's a great essay by Rich Hagee who created Closure about open source is not about you. Just because something in open source, I don't know, to respond to your issue and to pull requests. And I think some of the worries sometimes that people have about the groups is like, well, you know, if not, you're a part of this thing. Am I supposed to also listen to your thing and implement the thing that you said? So I think that's going to be a super interesting thing in a technology that is so new. You know, I feel like everybody, because there's so much venture money in like early stage companies and like, obviously the foundation model labs have raised so much money that they need to be on top of it.

1:32:26There's a lot more pressure, I think, from the community to try and be a part of it and like put their stake and be like, yeah, we've contributed that or whatnot. So I just think it's like a unique, compared to like the CNCF, for example, where the hyperscalers are kind of like around the clouds and we all know what those workloads look like and like nobody's really trying to influence. There's not like a OpenAI preferred thing versus like an Anthropic preferred thing. But it wasn't always so. So when we started CNCF, I got a call from, I think it was Urs Holtzel and Brian Stevens who were over at Google.

1:32:57as 2014, I want to say. And they're competing. Well, they weren't even competing. They weren't in the cloud business. And they wanted to be in that business. Amazon was hosting virtual machines on EC2, and they were the de facto leader. They said, we will give away Kubernetes, which was kind of the Borg, and they renamed it Kubernetes, to the Linux Foundation. And because we've never run a virtual machine, we think containers are a better way to scale cloud applications. We'll give you this tech, and it'll be helpful to us if the entire industry adopts containers and Kubernetes as the way to build and deploy applications.

1:33:37That was the strategy out of Google, and they contributed some serious IP that we all know today is awesome. But at the time, remember, Mesos was still a thing. Like PaaS was still a thing, right? Like, you know, Heroku, Cloud Foundry, even OpenStack, OpenStack, like virtual machines were still kind of a thing. So it wasn't clear what the abstraction layer for cloud computing was. But once the market started sort of piling on to Kubernetes, you know, like, oh, now Microsoft joined Cloud Native Computing Foundation. They're investing in Kubernetes and creating Kubernetes services. Oh, wait, Amazon's now investing in this?

1:34:16Then the consensus was really coming and built up here. I think there's a somewhat similar situation here with the caveat of saying like 10 times faster. Like just day one, so much momentum around MCP, so much interest in this. And then also 10 years of CNCF to sort of teach the developer community and the vendor community how to do this well, where, you know, investment is not mutually exclusive to great technical outcomes, I think has been super positive. So I think this is going to move super fast. Awesome. We don't want to keep you guys too long. I'm sure you've been on a media tour this week.

1:34:57What's maybe from each of you, like one thing you look forward in the new year from the foundation? so I don't really know what it's going to look like but I really look forward to like the next step like as David mentioned like it's being months of development and discussion whatever to bring us to this and there's this sense of I guess relief achievement that's like you know you made a foundation we're collaborating we created this open space it's great but the what next I'm super excited for the next technical contribution for the first AAIF event or night or conference or whatever form that ends up taking.

1:35:34Because there's another world where like bodies and foundations are created and then like eventually they get forgotten. And this is not that. This is really a beginning. And so I want to see it be healthy and grow. And I just don't know what comes next. So I'm most excited to see that in the new year. I think you're most excited. Like if I really take a neutral look at like what just happened in the industry with creating this, it's like you have Google, Microsoft, Amazon, um uh block bloomberg loudfair open air anthropic just a platinum member create a foundation i think it's just like this is actually quite quite cool and quite substantial and now it's just like now we have this like starting point of like what can we do with this and and to nick's point we don't i think there's a lot of like things we don't know yet and like things we need to figure out like for anthropic this is the first big foundation um we're recreating and we have to learn a lot here but I think it's just such an interesting like starting point and I'm just super excited for these like new when you when you start something new like what you can build with it and it's it's in a way of building something that I'm not familiar with so I'm super excited to learn about this and seeing what we can do with with this like I feel like quite unique vehicle now and like really driving the agentic like AI open source community forward and focusing on what we're some of these companies who are very competitive with each other have coming around and where we can build things together that is just benefiting and uplifting every user in the market and every developer in the market every builder in the market significantly that's what i'm really excited about um to see i definitely agree with both i think there's a lot of like opportunity to figure out what the structure does but let me give you something more specific that i think is like already in in coming up which is i i want to see how agents become asynchronous and I'm really tired of like reading through chat sessions and I want this to be a thing where I can go have like 20 agents working for me and actually see that come together.

1:37:37So I think that MCP is starting to like approach that answer and then we want to like figure out how to make those reference implementations and show people how they can actually get like another order of magnitude out of what AI can do for them. You don't enjoy pressing yes every five? The approve every three seconds. Bypass, bypass. dangerously skip permissions. Yeah, it turned off. I'm with you on that one. I think what I look forward to is, you know, the success stories of, you know, the organization that's implemented agentic technology in that way and hearing how it really impacted their business.

1:38:16I'm looking forward to stories about MCP startups that made a ton of money. I'm looking forward to stories like in CNCF this year, where CVS Pharmacy joined the Cloud Nature Computing Foundation, like a pharmacy company that's really a user and adopter of technology, sort of the late majority. I think we're going to start seeing organizations really, really use this tech impactfully, provide feedback back to the community. And the potential of the technology, I don't need to tell this crowd how huge it is, but we'll start to see that truly manifest, that is gonna be cool. Well, thank you all so much for joining and congrats on the launch.

1:39:06Thank you. Thanks for giving us.

From the publisher

One year ago, Anthropic launched the Model Context Protocol (MCP)—a simple, open standard to connect AI applications to the data and tools they need. Today, MCP has exploded from a local-only experiment into the de facto protocol for agentic systems, adopted by OpenAI, Microsoft, Google, Block, and hundreds of enterprises building internal agents at scale. And now, MCP is joining the newly formed Agentic AI Foundation (AAIF) under the Linux Foundation, alongside Block’s Goose coding agent, with founding members spanning the biggest names in AI and cloud infrastructure.

We sat down with David Soria Parra (MCP lead, Anthropic), Nick Cooper (OpenAI), Brad Howes (Block / Goose), and Jim Zemlin (Linux Foundation CEO) to dig into the one-year journey of MCP—from Thanksgiving hacking sessions and the first remote authentication spec to long-running tasks, MCP Apps, and the rise of agent-to-agent communication—and the behind-the-scenes story of how three competitive AI labs came together to donate their protocols and agents to a neutral foundation, why enterprises are deploying MCP servers faster than anyone expected (most of it invisible, internal, and at massive scale), what it takes to design a protocol that works for both simple tool calls and complex multi-agent orchestration, how the foundation will balance taste-making (curating meaningful projects) with openness (avoiding vendor lock-in), and the 2025 vision: MCP as the communication layer for asynchronous, long-running agents that work while you sleep, discover and install their own tools, and unlock the next order of magnitude in AI productivity.

We discuss:

* The one-year MCP journey: from local stdio servers to remote HTTP streaming, OAuth 2.1 authentication (and the enterprise lessons learned), long-running tasks, and MCP Apps (iframes for richer UI)

* Why MCP adoption is exploding internally at enterprises: invisible, internal servers connecting agents to Slack, Linear, proprietary data, and compliance-heavy workflows (financial services, healthcare)

* The authentication evolution: separating resource servers from identity providers, dynamic client registration, and why the March spec wasn’t enterprise-ready (and how June fixed it)

* How Anthropic dogfoods MCP: internal gateway, custom servers for Slack summaries and employee surveys, and why MCP was born from “how do I scale dev tooling faster than the company grows?”

* Tasks: the new primitive for long-running, asynchronous agent operations—why tools aren’t enough, how tasks enable deep research and agent-to-agent handoffs, and the design choice to make tasks a “container” (not just async tools)

* MCP Apps: why iframes, how to handle styles and branding, seat selection and shopping UIs as the killer use case, and the collaboration with OpenAI to build a common standard

* The registry problem: official registry vs. curated sub-registries (Smithery, GitHub), trust levels, model-driven discovery, and why MCP needs “npm for agents” (but with signatures and HIPAA/financial compliance)

* The founding story of AAIF: how Anthropic, OpenAI, and Block came together (spoiler: they didn’t know each other were talking to Linux Foundation), why neutrality matters, and how Jim Zemlin has never seen this much day-one inbound interest in 22 years

—

David Soria Parra (Anthropic / MCP)

* MCP: https://modelcontextprotocol.io

* https://uk.linkedin.com/in/david-soria-parra-4a78b3a

* https://x.com/dsp_

Nick Cooper (OpenAI)

* X: https://x.com/nicoaicopr

Brad Howes (Block / Goose)

* Goose: https://github.com/block/goose

Jim Zemlin (Linux Foundation)

* LinkedIn: https://www.linkedin.com/in/zemlin/

Agentic AI Foundation

* https://agenticai.foundation

Full Video Episode

Timestamps

00:00:00 Introduction: MCP's First Year and Foundation Launch00:01:17 MCP's Journey: From Launch to Industry Standard00:02:06 Protocol Evolution: Remote Servers and Authentication00:08:52 Enterprise Authentication and Financial Services00:11:42 Transport Layer Challenges: HTTP Streaming and Scalability00:15:37 Standards Development: Collaboration with Tech Giants00:34:27 Long-Running Tasks: The Future of Async Agents00:30:41 Discovery and Registries: Building the MCP Ecosystem00:30:54 MCP Apps and UI: Beyond Text Interfaces00:26:55 Internal Adoption: How Anthropic Uses MCP00:23:15 Skills vs MCP: Complementary Not Competing00:36:16 Community Events and Enterprise Learnings01:03:31 Foundation Formation: Why Now and Why Together01:07:38 Linux Foundation Partnership: Structure and Governance01:11:13 Goose as Reference Implementation01:17:28 Principles Over Roadmaps: Composability and Quality01:21:02 Foundation Value Proposition: Why Contribute01:27:49 Practical Investments: Events, Tools, and Community01:34:58 Looking Ahead: Async Agents and Real Impact



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