FastAPI-MCP vs MCP Python SDK
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Turns the endpoints of a FastAPI app into MCP tools that AI assistants can call, with auth.
Open source · MIT
Official Python library for building MCP servers and clients that connect AI apps to tools and data.
The short answer
Choose FastAPI-MCP if you need…
- Python developers who already have a FastAPI app and want AI assistants to use it
- Teams that want to reuse existing FastAPI authentication for MCP endpoints
- Developers who prefer minimal configuration and do not want to write MCP tools by hand
Choose MCP Python SDK if you need…
- Python developers who want to expose their own functions to an LLM app as MCP tools
- Developers building clients that connect to existing MCP servers
- Teams who need stdio, Streamable HTTP, or SSE transport support
- Anyone following the official MCP specification who wants a reference Python implementation
Side-by-side
| FastAPI-MCP | MCP Python SDK | |
|---|---|---|
| Type | Library | Library |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 12k | 24.7k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Install with a package manager | Install with a package manager |
| Main language | Python | Python |
| Last code update | 12 months ago | 4 days ago |
What each one is
FastAPI-MCP
FastAPI-MCP is a Python library that adds a Model Context Protocol (MCP) server to an existing FastAPI application, so AI tools such as Claude or Cursor can call your API endpoints as tools. It reuses your FastAPI routes, request and response schemas, and docs, and it can secure MCP access with your existing FastAPI dependencies.
MCP Python SDK
MCP (Model Context Protocol) is a standard way for LLM applications to access data and functionality. This Python SDK lets developers write a server that exposes tools, resources, and prompts, or a client that connects to such servers. Plain type-hinted Python functions are turned into MCP tools without writing JSON Schema or protocol code.
Best for
FastAPI-MCP
- Python developers who already have a FastAPI app and want AI assistants to use it
- Teams that want to reuse existing FastAPI authentication for MCP endpoints
- Developers who prefer minimal configuration and do not want to write MCP tools by hand
MCP Python SDK
- Python developers who want to expose their own functions to an LLM app as MCP tools
- Developers building clients that connect to existing MCP servers
- Teams who need stdio, Streamable HTTP, or SSE transport support
- Anyone following the official MCP specification who wants a reference Python implementation
Strengths
FastAPI-MCP
- Uses existing FastAPI dependencies for authentication and authorization
- Preserves request/response schemas and endpoint documentation from the FastAPI app
- Minimal setup: point it at a FastAPI app and mount it
MCP Python SDK
- Type hints and docstrings define the tool interface, so little boilerplate is needed
- Supports the standard transports: stdio, Streamable HTTP, and SSE
- Official project under the MIT license with 24k+ stars and documentation hosted on a dedicated site
Not ideal for
FastAPI-MCP
- Non-Python projects, since the README describes only a Python/FastAPI library
- People who need a managed service without running code; the README points to a hosted option at tadata.com but this entry does not evaluate it
- Anyone without an existing FastAPI app, since the library is an extension of FastAPI rather than a standalone tool
MCP Python SDK
- Non-programmers, since it requires writing Python code
- Projects that must run on Python versions below 3.11, as the README lists Python 3.11+ as a requirement
- Users looking for a ready-made end-user app rather than a developer library
Trade-offs
FastAPI-MCP
- Only useful if you already run or plan to run a FastAPI application
- README is truncated and does not detail every configuration option; the full documentation is on the homepage
- Latest release is v0.4.0 and the README does not state a stability guarantee
MCP Python SDK
- Requires Python 3.11 or newer
- The README is truncated and gives little detail beyond the quick-start examples; full details are on the external docs site
- Optional mcp[cli] extra is needed for the command-line tools
Getting started
FastAPI-MCP
Install with uv
uv add fastapi-mcpInstall with pip
pip install fastapi-mcpMCP Python SDK
Install with uv
uv add "mcp[cli]"Or install with pip
pip install "mcp[cli]"Frequently asked questions
What is the difference between FastAPI-MCP and MCP Python SDK?
FastAPI-MCP: Turns the endpoints of a FastAPI app into MCP tools that AI assistants can call, with auth. MCP Python SDK: Official Python library for building MCP servers and clients that connect AI apps to tools and data. FastAPI-MCP suits python developers who already have a fastapi app and want ai assistants to use it, while MCP Python SDK suits python developers who want to expose their own functions to an llm app as mcp tools.
Are FastAPI-MCP and MCP Python SDK free?
FastAPI-MCP: Free and open source. MCP Python SDK: Free and open source.
Is FastAPI-MCP or MCP Python SDK more popular?
MCP Python SDK has more GitHub stars (24.7k) than FastAPI-MCP (12k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to FastAPI-MCP and MCP Python SDK?
Other options people compare them with include mcp-use, Page Agent, OpenMythos, SQLModel, peewee.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.