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David Soria Parra from Anthropic argues that MCP (Model Context Protocol) is the key to connecting agents to tools and data in production, with 110 million monthly downloads—outpacing React's growth at the same stage. He lays out a 2026 connectivity stack combining Skills, MCP, and CLI/Computer Use, each suited for different needs, and emphasizes that best agents will use all three seamlessly. To improve client harnesses, he introduces Progressive Discovery—deferring tool loading via Tool Search to reduce context usage—and Programmatic Tool Calling, where models write scripts to compose tool outputs efficiently. Upcoming MCP protocol improvements include stateless transport (with Google) for easier scaling, async agent-to-agent tasks, enterprise features like Cross App Access and Server Discovery via well-known URLs, and a Skills-over-MCP extension for shipping usage instructions with servers. He calls for community feedback on these directions.
This overview is derived from the transcript and has not been independently fact-checked by AI Engineer.
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Key moments
An MCP application enables an agent to ship its own interface that works across Claude, ChatGPT, VS Code, and Cursor.
18 months ago, MCP consisted only of a spec document and locally-run SDKs largely written by Claude.
2025 was about exploring agents, but 2026 will be about putting them into production.
The 2026 connectivity stack for agents consists of Skills for domain knowledge, CLI for local coding, and MCP for rich semantics and enterprise.
Progressive Discovery with tool search defers tool loading to the moment a model needs it, reducing context window bloat.
Server authors should design tools for agent interaction rather than converting REST APIs one-to-one into MCP servers.
These moment labels are generated from the unreviewed transcript and may contain errors.
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