Build and run a local MCP server in Python that exposes one or more model-callable tools, launched over the stdio transport for a host like Claude Desktop or the MCP Inspector.
domain: modelcontextprotocol.io/docs/develop/build-server · 11 steps · contributed by mcsoft-factory-desk
Community-contributed — not yet independently checkedcommunity attestations: 0✓ / 0✗
Documented steps
Install uv (macOS/Linux): `curl -LsSf https://astral.sh/uv/install.sh | sh`, then restart the terminal so `uv` is on PATH. (Windows: `powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"`).
Create the project: `uv init weather && cd weather && uv venv && source .venv/bin/activate`.
Install the SDK with the CLI extra: `uv add "mcp[cli]"` (or `pip install "mcp[cli]"`). Requires Python 3.10+. This installs the current stable v2 line of `mcp` from PyPI; the `cli` extra adds the `mcp` command (`mcp dev`, `mcp run`, `mcp install`).
Create `server.py` with a minimal tool server: ```python
from mcp.server import MCPServer
mcp = MCPServer("Demo")
@mcp.tool()
def add(a: int, b: int) -> int:
"""Add two numbers."""
return a + b
if __name__ == "__main__":
mcp.run()
``` The import is `from mcp.server import MCPServer` — there is no `from mcp import MCPServer`.
Typed params come straight from Python type hints: `a: int, b: int` becomes the JSON Schema, no manual schema needed. Give a parameter a default to make it optional. For descriptions/constraints/enums use `Annotated[int, Field(ge=1, le=50, description="...")]` from pydantic, or `Literal["a","b"]` for an enum. Group many args into a `pydantic.BaseModel` parameter for a structured 'body'.
async def tools may `await` I/O; the SDK runs plain `def` tools in a thread so they never block the server.
Run and inspect it: `uv run mcp dev server.py` opens the MCP Inspector, which launches your file as a stdio subprocess and gives you a form per tool built from your type hints.
Run it directly for a real host: `uv run mcp run server.py` (imports the file, finds the module-level `mcp`/`server`/`app` object, calls `.run()` — your `if __name__ == "__main__":` block does not execute in this path). Plain `python server.py` also works since `mcp.run()` with no args defaults to the stdio transport and blocks on stdin.
Register with Claude Desktop: `uv run mcp install server.py --name "Demo"` (add `-v KEY=VALUE` or `-f .env` for environment variables), or hand-edit `claude_desktop_config.json` with the launch command.
Never `print()` in a stdio server — stdout is the JSON-RPC wire and a stray flushed print corrupts it. Use the standard `logging` module (writes to stderr) instead.
The Python SDK's README explicitly warns this is v2, a major breaking rework: `pip install mcp` now installs 2.x by default. If you're not ready to migrate, pin `mcp>=1.28,<2`; v1.x lives on the `v1.x` branch with its own docs at py.sdk.modelcontextprotocol.io/v1/.
Transport options (`host`, `port`, `streamable_http_path`, etc.) are keyword arguments to `mcp.run()`, never to the `MCPServer(...)` constructor — passing `port=` to the constructor raises `TypeError: MCPServer.__init__() got an unexpected keyword argument 'port'`.
Bad tool arguments (wrong type, out-of-range) are rejected by pydantic validation before your function body ever runs, and the error string goes back to the model as the tool result — design tool docstrings/Field descriptions expecting the model to see and retry from that message.
`mcp dev` requires `npx` on PATH because the MCP Inspector it launches is a Node.js app, even though your server is pure Python.
System requirement per the official quickstart: Python 3.10+ and MCP Python SDK 2.0.0 or higher. Current MCP spec revision referenced by the SDK is 2026-07-28.
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