Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
FastAPI-MCP is a Python library that automatically converts existing FastAPI endpoints into Model Context Protocol tools, making them available to MCP-compatible clients such as Claude Desktop, Cursor, and Windsurf. Developers install it via pip or uv, instantiate a `FastApiMCP` object pointing at their FastAPI app, call `mcp.mount()`, and the MCP server becomes accessible at `/mcp` on the same base URL with no further configuration required. Rather than simply parsing an OpenAPI schema, the library integrates natively with FastAPI, using its ASGI interface to communicate directly without additional HTTP round-trips and preserving existing `Depends()`-based authentication and authorization logic without rewriting it. Request and response model schemas, along with Swagger documentation, carry over automatically to the generated tools. The server can be mounted alongside the existing app or deployed separately. Python 3.10 or higher is required, with 3.12 recommended. The library suits backend developers who want to expose their existing API logic to LLM-driven workflows without maintaining a parallel service or duplicating security code.
- ✓Open-source license (MIT)
- ✓Healthy fork ratio
- ✓Clear description
- ✓Topics declared
- ✓Mature repo (>1y old)
- ✓Documented (README)
- !Inactive (>180d)
claude mcp add fastapi-mcp -- python -m fastapi-mcp{
"mcpServers": {
"fastapi-mcp": {
"command": "python",
"args": ["-m", "fastapi-mcp"]
}
}
}Resumen de MCP Servers
<p align="center"><a href="https://github.com/tadata-org/fastapi_mcp"><img src="https://github.com/user-attachments/assets/7e44e98b-a0ba-4aff-a68a-4ffee3a6189c" alt="fastapi-to-mcp" height=100/></a></p> <div align="center"> <span style="font-size: 0.85em; font-weight: normal;">Built by <a href="https://tadata.com">Tadata</a></span> </div> <h1 align="center"> FastAPI-MCP </h1> <div align="center"> <a href="https://trendshift.io/repositories/14064" target="_blank"><img src="https://trendshift.io/api/badge/repositories/14064" alt="tadata-org%2Ffastapi_mcp | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> </div> <p align="center">Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!</p> <div align="center"> [](https://pypi.org/project/fastapi-mcp/) [](https://pypi.org/project/fastapi-mcp/) [](#) [](https://github.com/tadata-org/fastapi_mcp/actions/workflows/ci.yml) [](https://codecov.io/gh/tadata-org/fastapi_mcp) </div> <p align="center"><a href="https://github.com/tadata-org/fastapi_mcp"><img src="https://github.com/user-attachments/assets/b205adc6-28c0-4e3c-a68b-9c1a80eb7d0c" alt="fastapi-mcp-usage" height="400"/></a></p> ## Features - **Authentication** built in, using your existing FastAPI dependencies! - **FastAPI-native:** Not just another OpenAPI -> MCP converter - **Zero/Minimal configuration** required - just point it at your FastAPI app and it works - **Preserving schemas** of your request models and response models - **Preserve documentation** of all your endpoints, just as it is in Swagger - **Flexible deployment** - Mount your MCP server to the same app, or deploy separately - **ASGI transport** - Uses FastAPI's ASGI interface directly for efficient communication ## Hosted Solution If you prefer a managed hosted solution check out [tadata.com](https://tadata.com). ## Installation We recommend using [uv](https://docs.astral.sh/uv/), a fast Python package installer: ```bash uv add fastapi-mcp ``` Alternatively, you can install with pip: ```bash pip install fastapi-mcp ``` ## Basic Usage The simplest way to use FastAPI-MCP is to add an MCP server directly to your FastAPI application: ```python from fastapi import FastAPI from fastapi_mcp import FastApiMCP app = FastAPI() mcp = FastApiMCP(app) # Mount the MCP server directly to your FastAPI app mcp.mount() ``` That's it! Your auto-generated MCP server is now available at `https://app.base.url/mcp`. ## Documentation, Examples and Advanced Usage FastAPI-MCP provides [comprehensive documentation](https://fastapi-mcp.tadata.com/). Additionaly, check out the [examples directory](examples) for code samples demonstrating these features in action. ## FastAPI-first Approach FastAPI-MCP is designed as a native extension of FastAPI, not just a converter that generates MCP tools from your API. This approach offers several key advantages: - **Native dependencies**: Secure your MCP endpoints using familiar FastAPI `Depends()` for authentication and authorization - **ASGI transport**: Communicates directly with your FastAPI app using its ASGI interface, eliminating the need for HTTP calls from the MCP to your API - **Unified infrastructure**: Your FastAPI app doesn't need to run separately from the MCP server (though [separate deployment](https://fastapi-mcp.tadata.com/advanced/deploy#deploying-separately-from-original-fastapi-app) is also supported) This design philosophy ensures minimum friction when adding MCP capabilities to your existing FastAPI services. ## Development and Contributing Thank you for considering contributing to FastAPI-MCP! We encourage the community to post Issues and create Pull Requests. Before you get started, please see our [Contribution Guide](CONTRIBUTING.md). ## Community Join [MCParty Slack community](https://join.slack.com/t/themcparty/shared_invite/zt-30yxr1zdi-2FG~XjBA0xIgYSYuKe7~Xg) to connect with other MCP enthusiasts, ask questions, and share your experiences with FastAPI-MCP. ## Requirements - Python 3.10+ (Recommended 3.12) - uv ## License MIT License. Copyright (c) 2025 Tadata Inc.
Lo que la gente pregunta sobre fastapi_mcp
¿Qué es tadata-org/fastapi_mcp?
+
tadata-org/fastapi_mcp es mcp servers para el ecosistema de Claude AI. Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth! Tiene 11.9k estrellas en GitHub y se actualizó por última vez 6mo ago.
¿Cómo se instala fastapi_mcp?
+
Puedes instalar fastapi_mcp clonando el repositorio (https://github.com/tadata-org/fastapi_mcp) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.
¿Es seguro usar tadata-org/fastapi_mcp?
+
Nuestro agente de seguridad ha analizado tadata-org/fastapi_mcp y le ha asignado un Trust Score de 90/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.
¿Quién mantiene tadata-org/fastapi_mcp?
+
tadata-org/fastapi_mcp es mantenido por tadata-org. La última actividad registrada en GitHub es de 6mo ago, con 155 issues abiertos.
¿Hay alternativas a fastapi_mcp?
+
Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.
Despliega fastapi_mcp en tu cloud
Lleva este repo a producción en minutos. Cada plataforma genera su propio entorno con variables de entorno editables.
¿Mantienes este repo? Añade un badge a tu README
Pega el badge en tu README de GitHub para mostrar que está auditado por ClaudeWave. Cada badge enlaza de vuelta a esta página y muestra el Trust Score actual.
[](https://claudewave.com/repo/tadata-org-fastapi-mcp)<a href="https://claudewave.com/repo/tadata-org-fastapi-mcp"><img src="https://claudewave.com/api/badge/tadata-org-fastapi-mcp" alt="Featured on ClaudeWave: tadata-org/fastapi_mcp" width="320" height="64" /></a>Más MCP Servers
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
An open-source AI agent that brings the power of Gemini directly into your terminal.
The fastest path to AI-powered full stack observability, even for lean teams.
🕷️ An adaptive Web Scraping framework that handles everything from a single request to a full-scale crawl!
⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载,你的 AI 舆情监控助手与热点筛选工具!聚合多平台热点 + RSS 订阅,支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机,也支持接入 MCP 架构,赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ,数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。