iflow-mcp_maxim-saplin-mcp_safe_local_python_executor

# Safe Local Python Executor An MCP server (stdio transport) that wraps Hugging Face's [`LocalPythonExecutor`](https://github.com/huggingface/smolagents/blob/main/src/smolagents/local_python_executor.py) (from the [`smolagents`](https://huggingface.co/docs/smolagents/en/index) framework). It is a custom Python runtime that provides basic isolation/security when running Python code generated by LLMs locally. It does not require Docker or VM. This package allows to expose the Python executor via MCP (Model Context Protocol) as a tool for LLM apps like Claude Desktop, Cursor or any other MCP compatible client. In case of Claude Desktop this tool is an easy way to add a missing Code Interpreter (available as a plugin in ChatGPT for quite a while already). <img width="1032" alt="image" src="https://github.com/user-attachments/assets/3b820bfc-970a-4315-8f2d-970591c6fdae" /> ## Features - Exposes `run_python` tool - Safer execution of Python code compared to direct use of Python `eva()l` - Ran via uv in Python venv - No file I/O ops are allowed - Restricted list of imports - collections - datetime - itertools - math - queue - random - re - stat - statistics - time - unicodedata ## Security Be careful with execution of code produced by LLM on your machine, stay away from MCP servers that run Python via command line or using `eval()`. The safest option is using a VM or a docker container, though it requires some effort to set-up, consumes resources/slower. There're 3rd party servcices providing Python runtime, though they require registration, API keys etc. `LocalPythonExecutor` provides a good balance between direct use of local Python environment (which is easier to set-up) AND remote execution in Dokcer container or a VM/3rd party service (which is safe). Hugginng Face team has invested time into creating a quick and safe option to run LLM generated code used by their code agents. This MCP server builds upon it: >To ad…