I Described a Multi-Agent, Multi-Model System in Plain English. It Was Built in Seconds. Part 5/5

Last time: Claude helped write this series. I gave it access to our docs at docs.backboard.io, it read them itself, and it produced a series describing its own API's limitations. That was the hook. TLDR - SOOOO Easy. -> Backboard MCP Copy and Paste this to Claude Code: claude mcp add backboard-docs --transport http https://backboard-docs.docsalot.dev/api/mcp This post is where that story closes. Anthropic's API is stateless. We've been through all of that. You've seen what it takes to build state management, memory, RAG, multi-model routing, and parallel agent networks on top of it. Parts 1 through 4 are a map of that infrastructure. Part 5 is about what happens when you don't have to build any of it manually at all. What MCP is, and why it matters MCP stands for Model Context Protocol. It's an open standard created to solve a specific problem: how do you give an AI agent structured, safe access to external tools and APIs? Before MCP, every integration between an AI and an external ser