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Why we built—and donated—the Model Context Protocol (MCP)

Anthropic's Stuart Ritchie speaks with co-creator David Soria Parra about the development of the Model Context Protocol (MCP), an open standard to connect AI to external tools and services—and why Anthropic is donating it to the Linux Foundation. 00:00 - What is MCP? 01:21 - The problem MCP solves 02:46 - The USB-C analogy 03:45 - How MCP began 05:36 - What makes MCP different 08:05 - Community adoption 09:54 - Standards without mandates 11:05 - From Anthropic hackathon to Hacker News 13:37 - The decision to open source 15:18 - Donating MCP to the Linux Foundation 17:27 - The Agentic AI Foundation 20:34 - Criticisms of MCP 28:21 - The future of MCP 30:58 - What have people built with MCP? 32:53 - Advice for non-developers 34:58 - What David is most proud of

David Soria ParraguestStuart Ritchiehost
Dec 10, 202535mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

MCP unifies AI tool integrations and moves to neutral stewardship

  1. MCP is an open protocol that lets AI applications connect to external tools and services without rewriting integrations for each model or client.
  2. The project started as an internal effort to make Claude more useful in day-to-day workflows, then rapidly grew through an internal hackathon and strong community adoption after open-sourcing.
  3. Anthropic is donating MCP (including trademarks and related legal governance) to the Linux Foundation to prevent future “rug pulls” and increase trust among competing ecosystem players.
  4. The conversation highlights real criticisms—especially security risks from third-party tools, context bloat from too many tool descriptions, and scaling challenges from stateful sessions—and describes mitigations in clients and model tooling.
  5. Future work includes scaling/statefulness improvements, long-running “Tasks,” richer UI delivered over MCP (“MCP Apps”), and community growth via the Linux Foundation’s Agentic AI Foundation.

IDEAS WORTH REMEMBERING

5 ideas

MCP’s core value is “write once, integrate everywhere.”

Instead of building separate connectors for each model provider and each client (IDE, desktop app, etc.), MCP standardizes the interface so a single server integration can work across many environments.

Standards can emerge from usage, not mandates.

MCP gained traction by being practical and immediately useful—released openly, adopted by real products, and iterated with community input—rather than waiting for formal standard bodies first.

Neutral governance increases ecosystem trust and long-term stability.

Donating MCP to the Linux Foundation transfers trademarks and legal stewardship away from Anthropic, reducing fears of license changes or withdrawal and making it safer for competitors and enterprises to invest.

Security risk is less “the protocol” and more “unknown tools + agentic power.”

Because anyone can publish tools/servers, prompt injection and data exfiltration become realistic threats; mitigations involve model/provider safeguards, client UX/permissions, and protocol-level hints like read vs write operations.

Registries enable discovery but create supply-chain challenges.

An open registry (like npm/PyPI) accelerates adoption, but “anyone can publish” also raises malware and trust issues; sub-registries and vetting layers can add filtering and security checks.

WORDS WORTH SAVING

5 quotes

What MCP tries to accomplish is giving this, like, brain that you have… really the limbs into the world.

— David Soria Parra

You’d only have to write the integration once instead of having to write the integration for every model provider over and over.

— David Soria Parra

Nobody’s mandating MCP. Just yet.

— David Soria Parra

If you bet on MCP, nobody will change that on you in the future.

— David Soria Parra

Preferably… you never have to read the word MCP.

— David Soria Parra

Why LLMs need connections to real-world softwareOne-integration-many-clients protocol designUSB-C analogy for standard connectorsOpen-source development and community-driven standardizationAdoption by IDEs, platforms, and model providersDonation to Linux Foundation and trademark neutralitySecurity, prompt injection, and supply-chain concernsContext bloat and tool discovery approachesStateful sessions and scaling constraintsTasks, agent-to-agent workflows, and MCP Apps UI

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