MCP Python SDK

<strong>Python implementation of the Model Context Protocol (MCP)</strong>

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MCP Python SDK

Overview

The Model Context Protocol allows applications to provide context for LLMs in a standardized way, separating the concerns of providing context from the actual LLM interaction. This Python SDK implements the full MCP specification, making it easy to:

Build MCP clients that can connect to any MCP server
Create MCP servers that expose resources, prompts and tools
Use standard transports like stdio, SSE, and Streamable HTTP
Handle all MCP protocol messages and lifecycle events

Installation

Adding MCP to your python project

We recommend using uv to manage your Python projects.

If you haven't created a uv-managed project yet, create one:

uv init mcp-server-demo
cd mcp-server-demo

Then add MCP to your project dependencies:

uv add "mcp[cli]"

Alternatively, for projects using pip for dependencies:

pip install "mcp[cli]"

Running the standalone MCP development tools

To run the mcp command with uv:

uv run mcp

Quickstart

Let's create a simple MCP server that exposes a calculator tool and some data:

"""
FastMCP quickstart example.

Run from the repository root:
    uv run examples/snippets/servers/fastmcp_quickstart.py
"""

from mcp.server.fastmcp import FastMCP

# Create an MCP server
mcp = FastMCP("Demo", json_response=True)


# Add an addition tool
@mcp.tool()
def add(a: int, b: int) -> int:
    """Add two numbers"""
    return a + b


# Add a dynamic greeting resource
@mcp.resource("greeting://{name}")
def get_greeting(name: str) -> str:
    """Get a personalized greeting"""
    return f"Hello, {name}!"


# Add a prompt
@mcp.prompt()
def greet_user(name: str, style: str = "friendly") -> str:
    """Generate a greeting prompt"""
    styles = {
        "friendly": "Please write a warm, friendly greeting",
        "formal": "Please write a formal, professional greeting",
        "casual": "Please write a casual, relaxed greeting",
    }

    return f"{styles.get(style, styles['friendly'])} for someone named {name}."


# Run with streamable HTTP transport
if __name__ == "__main__":
    mcp.run(transport="streamable-http")

Full example: examples/snippets/servers/fastmcp_quickstart.py

You can install this server in Claude Code and interact with it right away. First, run the server:

uv run --with mcp examples/snippets/servers/fastmcp_quickstart.py

Then add it to Claude Code:

claude mcp add --transport http my-server http://localhost:8000/mcp

Alternatively, you can test it with the MCP Inspector. Start the server as above, then in a separate terminal:

npx -y @modelcontextprotocol/inspector

In the inspector UI, connect to http://localhost:8000/mcp.

What is MCP?

The Model Context Protocol (MCP) 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 specifically designed for LLM interactions. MCP servers can:

Expose data through Resources (think of these sort of like GET endpoints; they are used to load information into the LLM's context)
Provide functionality through Tools (sort of like POST endpoints; they are used to execute code or otherwise produce a side effect)
Define interaction patterns through Prompts (reusable templates for LLM interactions)
And more!

Core Concepts

Server

The FastMCP server is your core interface to the MCP protocol. It handles connection management, protocol compliance, and message routing:

"""Example showing lifespan support for startup/shutdown with strong typing."""

from collections.abc import AsyncIterator
from contextlib import asynccontextmanager
from dataclasses import dataclass

from mcp.server.fastmcp import Context, FastMCP
from mcp.server.session import ServerSession


# Mock database class for example
class Database:
    """Mock database class for example."""

    @classmethod
    async def connect(cls) -> "Database":
        """Connect to database."""
        return cls()

    async def disconnect(self) -> None:
        """Disconnect from database."""
        pass

    def query(self) -> str:
        """Execute a query."""
        return "Query result"


@dataclass
class AppContext:
    """Application context with typed dependencies."""

    db: Database


@asynccontextmanager
async def app_lifespan(server: FastMCP) -> AsyncIterator[AppContext]:
    """Manage application lifecycle with type-safe context."""
    # Initialize on startup
    db = await Database.connect()
    try:
        yield AppContext(db=db)
    finally:
        # Cleanup on shutdown
        await db.disconnect()


# Pass lifespan to server
mcp = FastMCP("My App", lifespan=app_lifespan)


# Access type-safe lifespan context in tools
@mcp.tool()
def query_db(ctx: Context[ServerSession, AppContext]) -> str:
    """Tool that uses initialized resources."""
    db = ctx.request_context.lifespan_context.db
    return db.query()

Full example: examples/snippets/servers/lifespan_example.py

Resources

Resources are how you expose data to LLMs. They're similar to GET endpoints in a REST API - they provide data but shouldn't perform significant computation or have side effects:

from mcp.server.fastmcp import FastMCP

mcp = FastMCP(name="Resource Example")


@mcp.resource("file://documents/{name}")
def read_document(name: str) -> str:
    """Read a document by name."""
    # This would normally read from disk
    return f"Content of {name}"


@mcp.resource("config://settings")
def get_settings() -> str:
    """Get application settings."""
    return """{
  "theme": "dark",
  "la

mcp

Description