Building MCP Servers with FastMCP: Stop Writing Boilerplate, Start Writing Tools

If you've spent time wiring up AI agents to external systems, you've probably hit the same wall I did: every integration is a one-off. You write a custom function, shove it into a tool definition, hope the schema is right, debug JSON blobs, and repeat. It works, but it doesn't compose . Nothing is reusable. Every new agent starts from scratch. MCP — the Model Context Protocol — is Anthropic's answer to that. It's a standardized way for language models to talk to external tools, data sources, and services. Think of it like a universal adapter: you build a server once, and any MCP-compatible client can use it. Claude, Claude Code, and a growing list of other tools all speak MCP natively. The protocol itself is straightforward. But writing a raw MCP server is not. You're dealing with JSON-RPC, capability negotiation, input schema generation, and transport layers before you've written a single line of actual business logic. That's where FastMCP comes in. What FastMCP Actually Does FastMCP