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# MCP Python SDK
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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.
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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 ](https://modelcontextprotocol.io ).
## Quick Example
Here's a simple MCP server that exposes a tool, resource, and prompt:
```python title="server.py"
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from mcp.server.mcpserver import MCPServer
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mcp = MCPServer("Test Server", json_response=True)
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@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}."
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if __name__ == "__main__":
mcp.run(transport="streamable-http")
` ``
Run the server:
` ``bash
uv run --with mcp server.py
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` ``
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Then open the [MCP Inspector](https://github.com/modelcontextprotocol/inspector) and connect to ` http://localhost:8000/mcp`:
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` ``bash
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npx -y @modelcontextprotocol/inspector
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` ``
## Getting Started
<!-- TODO(Marcelo): automatically generate the follow references with a header on each of those files. -->
1. * * [Install ](installation.md )** the MCP SDK
2. * * [Learn concepts ](concepts.md )** - understand the three primitives and architecture
3. * * [Explore authorization ](authorization.md )** - add security to your servers
4. * * [Use low-level APIs ](low-level-server.md )** - for advanced customization
## API Reference
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Full API documentation is available in the [API Reference ](api/mcp/index.md ).
