MCP Co-Creator on the Next Wave of LLM Innovation

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May 2, 2025

David Soria Parra, creator of the Model Context Protocol (MCP) at Anthropic, shares his insights on revolutionizing AI applications. He discusses how MCP enables seamless integration of AI with existing tools, likening it to the API ecosystem. The conversation highlights innovative uses of MCP in creative tools like Blender and Ableton, fostering new artistic expressions. Furthermore, they delve into how agents communicate, balancing natural and programming languages, and underscore the importance of community participation in evolving this groundbreaking protocol.

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ANECDOTE

Practical and Fun MCP Uses

Yoko Li built an MCP server that texts her husband to explain why dinner is late, showing practical applications of MCP.
Another fun project used Philips Hue lights to communicate LLM task completion in Morse code, amusingly confusing her cats.

INSIGHT

Sampling Enables Model-Independence

MCP's 'sampling' feature allows an MCP server to request LLM completions from the client model, enabling model-independent servers.
This supports building richer agentic loops and summarization without binding servers to specific LLM APIs.

INSIGHT

Chaining MCP Servers and Clients

MCP servers and clients can chain and nest, creating graphs of agentic loops orchestrating multiple tools and workflows.
This composability opens powerful possibilities for user-defined multi-server agent systems controlling diverse tasks.

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In this episode of AI + a16z, Anthropic's David Soria Parra — who created MCP (Model Context Protocol) along with Justin Spahr-Summers — sits down with a16z's Yoko Li to discuss the project's inception, exciting use cases for connecting LLMs to external sources, and what's coming next for the project. If you're unfamiliar with the wildly popular MCP project, this edited passage from their discussion is a great starting point to learn:

David: "MCP tries to enable building AI applications in such a way that they can be extended by everyone else that is not part of the original development team through these MCP servers, and really bring the workflows you care about, the things you want to do, to these AI applications. It's a protocol that just defines how whatever you are building as a developer for that integration piece, and that AI application, talk to each other.

"It's a very boring specification, but what it enables is hopefully ... something that looks like the current API ecosystem, but for LLM interactions."

Yoko: "I really love the analogy with the API ecosystem, because they give people a mental model of how the ecosystem evolves ... Before, you may have needed a different spec to query Salesforce versus query HubSpot. Now you can use similarly defined API schema to do that.

"And then when I saw MCP earlier in the year, it was very interesting in that it almost felt like a standard interface for the agent to interface with LLMs. It's like, 'What are the set of things that the agent wants to execute on that it has never seen before? What kind of context does it need to make these things happen?' When I tried it out, it was just super powerful and I no longer have to build one tool per client. I now can build just one MCP server, for example, for sending emails, and I use it for everything on Cursor, on Claude Desktop, on Goose."

Learn more:

A Deep Dive Into MCP and the Future of AI Tooling

What Is an AI Agent?

Benchmarking AI Agents on Full-Stack Coding

Agent Experience: Building an Open Web for the AI Era

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David Soria Parra

Yoko Li

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