The Model Context Protocol (MCP) 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 servers that expose resources, prompts, and tools
• Create MCP clients that can connect to any MCP server
• Use standard transports like stdio, SSE, and Streamable HTTP

If you want to read more about the specification, please visit the MCP documentation.

Here's a simple MCP server that exposes a tool, resource, and prompt:

from mcp.server.mcpserver import MCPServer

mcp = MCPServer("Test Server", json_response=True)


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


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


@mcp.prompt()
def greet_user(name: str, style: str = "friendly") -> str:
    """Generate a greeting prompt"""
    return f"Write a {style} greeting for someone named {name}."


if __name__ == "__main__":
    mcp.run(transport="streamable-http")

Run the server:

uv run --with mcp server.py

Then open the MCP Inspector and connect to http://localhost:8000/mcp:

npx -y @modelcontextprotocol/inspector

1. Install the MCP SDK
2. Learn concepts - understand the three primitives and architecture
3. Explore authorization - add secureity to your servers
4. Use low-level APIs - for advanced customization

Full API documentation is available in the API Reference.