ai-devkit vs fastapi_mcp
ai-devkit: AI DevKit is a local-first operating layer for teams running several coding agents. One .ai-devkit.json reconciles skills, MCP and setup across Claude Code, Codex CLI, Gemini CLI, opencode, Pi, Cursor, Copilot and others; agent console is a live TUI for running sessions; agent send routes prompts, logs or stdin to a running agent; and a local SQLite memory is searched over MCP when needed. A dev-lifecycle skill guides requirements, design, planning, implementation, testing and review.; fastapi_mcp: FastAPI-MCP allows you to expose your existing FastAPI endpoints as Model Context Protocol (MCP) tools. It offers native integration with FastAPI, including built-in authentication using existing dependencies, and preserves schemas and documentation.
TL;DR
Keeping one setup across Claude Code, Codex and Cursor in a team repo
- You already have a FastAPI application and want to expose its endpoints as MCP tools while reusing your existing FastAPI authentication dependencies and Swagger schemas.
- You want to mount the MCP server directly onto your ASGI app or deploy it separately under an MIT license.
- You are building a standalone MCP server from scratch rather than wrapping a FastAPI app; use FastMCP or the official MCP Python SDK.
- You need an actively updated repository (last push was November 2025).
Side-by-Side Comparison
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