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Building Agents with Model Context Protocol - Full Workshop with Mahesh Murag of Anthropic
Takeaway
MCP turns custom AI integrations into a standardized client-server protocol so any compatible client can talk to any tool with zero glue code.
Summary
- Anthropic's Mahesh Murag presents MCP as an open protocol standardizing how AI apps connect to external tools/data, analogous to APIs for web or LSP for IDEs.
- MCP exposes three primitives: tools (model-controlled), resources (app-controlled data), and prompts (user-controlled templates), collapsing the N×M integration problem.
- Adoption shown via ~1100 community-built servers, first-party integrations from Cursor, Windsurf, Goose, and enterprise teams owning vector-DB or Salesforce servers.
- Workshop covers building clients/servers, sampling, composability, and roadmap items like remote servers, OAuth, registry, and agent-of-agents patterns.
mcpagentsanthropic
Original description
The Model Context Protocol is a universal, open standard for connecting AI systems with data sources, replacing fragmented integrations with a single protocol. This workshop from Anthropic -- the creators of MCP -- talks about the philosophy behind MCP, its impact on the broader ecosystem since launch, and how developers can use it to build context-rich AI apps and agentic experiences. 00:00 What is MCP? 9:39 Building with MCP 26:25 MCP & Agents 1:13:15 What's next for MCP? Recorded live at workshop day from the AI Engineer Summit 2025 in NY. Learn more at https://ai.engineer and purchase tickets to our next event, the AI Engineer World's Fair, in SF June 3 - 5 here: https://ti.to/software-3/ai-engineer-worlds-fair-2025 About the instructor Mahesh is a Member of Technical Staff on Anthropic's Applied AI team, focused on Model Context Protocol, agents, and helping make Claude more useful to enterprises. He was previously a Product Manager at Scale AI & Tecton and did research at UC Berkeley on how self-driving cars impact traffic systems.