Model Context Protocol (MCP) is a standardized way for AI models to connect to external tools and data sources, solving the N×M integration problem. The post covers MCP's architecture (hosts, clients, servers), three primitives (tools, resources, prompts), transport methods (stdio and Streamable HTTP), and practical setup in Claude Code, Cursor, and VS Code. It also covers the broader three-layer agentic stack (MCP + A2A + WebMCP), security risks including tool poisoning, supply chain attacks, and real CVEs, plus a TypeScript example for building a custom MCP server. Industry adoption is now near-universal with the Linux Foundation's Agentic AI Foundation housing the spec.
Table of contents
What MCP Actually Is (Without the Buzzwords)The Architecture in Plain EnglishWhy This Matters Right NowSetting Up MCP: The Practical PartMCP Servers Worth InstallingThe Three-Layer Protocol StackSecurity: The Part Nobody Wants to Talk AboutBuilding Your Own MCP ServerWhere This Is GoingGetting Started Today9 Impressions