modelcontextprotocol/python-sdk

Python implementation of the Model Context Protocol (MCP)
[![PyPI][pypi-badge]][pypi-url]
[![MIT licensed][mit-badge]][mit-url]
[![Python Version][python-badge]][python-url]
[![Documentation][docs-badge]][docs-url]
[![Protocol][protocol-badge]][protocol-url]
[![Specification][spec-badge]][spec-url]
## Documentation
The documentation lives at .
It has a Get started guide, What's new in v2, the API reference, and the migration guide.
## What is MCP?
The Model Context Protocol lets you build servers that expose data and functionality to LLM applications in a secure, standardized way. Think of it like a web API, but designed for LLM interactions. With this SDK you can:
Build MCP servers that expose tools, resources, and prompts to any MCP host
Build MCP clients that connect to any MCP server
Speak every standard transport: stdio, Streamable HTTP, and SSE
## Requirements
Python 3.11+.
## Installation
bash
uv add "mcp[cli]" # or: pip install "mcp[cli]"
The cli extra adds the mcp command-line tool (mcp dev, mcp run, mcp install) on top of the SDK; install plain mcp if you don't need it. For one-off commands, uv run --with "mcp[cli]" mcp ... works without a project.
## A server in 15 lines
Create a server.py:
python
from mcp.server import MCPServer
mcp = MCPServer("Demo")
@mcp.tool()
def add(a: int, b: int) -> int:
"""Add two numbers."""
return a + b
@mcp.resource("greeting://{name}")
def greeting(name: str) -> str:
"""Greet someone by name."""
return f"Hello, {name}!"
Full example: docssrc/index/tutorial001.py
That's a complete MCP server: one tool, one templated resource. Open it in the MCP Inspector:
bash
uv run mcp dev server.py
Call add with a=1, b=2 and you get 3 back.
Notice what you did not write: no JSON Schema (a: int, b: int is the schema), no request parsing, no validation code, no protocol handling. Two type-hinted Python functions and a docstring.
Get started takes it from here.
## A client in 10 lines
The same package is a full MCP client. Serve server.py over HTTP:
bash
uv run mcp run server.py --transport streamable-http
then point a Client at it:
python
import asyncio
from mcp import Client
async def main() -> None:
async with Client("http://localhost:8000/mcp") as client:
result = await client.calltool("add", {"a": 1, "b": 2})
print(result.structuredcontent) # {'result': 3}
asyncio.run(main())
A URL means Streamable HTTP, the transport you deploy. Client can also launch a local server as a stdio subprocess or take any custom transport; Clients has the rest.
## Contributing
We are passionate about supporting contributors of all levels of experience and would love to see you get involved in the project. See the contributing guide to get started.