MCP Run Python

Model Context Protocol server to run Python code in a sandbox.

The code is executed using Pyodide in Deno and is therefore isolated from the rest of the operating system.

See <https: ai.pydantic.dev="" mcp="" run-python=""></https:> for complete documentation.

The server can be run with deno installed using:

deno run \
  -N -R=node_modules -W=node_modules --node-modules-dir=auto \
  jsr:@pydantic/mcp-run-python [stdio|sse|warmup]

where:

-N -R=node_modules -W=node_modules (alias of --allow-net --allow-read=node_modules --allow-write=node_modules) allows network access and read+write access to ./node_modules. These are required so pyodide can download and cache the Python standard library and packages
--node-modules-dir=auto tells deno to use a local node_modules directory
stdio runs the server with the Stdio MCP transport — suitable for running the process as a subprocess locally
sse runs the server with the SSE MCP transport — running the server as an HTTP server to connect locally or remotely
warmup will run a minimal Python script to download and cache the Python standard library. This is also useful to check the server is running correctly.

Here's an example of using @pydantic/mcp-run-python with Pydantic AI:

from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStdio

import logfire

logfire.configure()
logfire.instrument_mcp()
logfire.instrument_pydantic_ai()

server = MCPServerStdio('deno',
    args=[
        'run',
        '-N',
        '-R=node_modules',
        '-W=node_modules',
        '--node-modules-dir=auto',
        'jsr:@pydantic/mcp-run-python',
        'stdio',
    ])
agent = Agent('claude-3-5-haiku-latest', toolsets=[server])


async def main():
    async with agent:
        result = await agent.run('How many days between 2000-01-01 and 2025-03-18?')
    print(result.output)
    #&gt; There are 9,208 days between January 1, 2000, and March 18, 2025.w

if __name__ == '__main__':
    import asyncio
    asyncio.run(main())