Python Runner MCP Server
About
A Python code execution server built on the FastMCP framework, designed for data science and machine learning workflows. It executes Python code in isolated namespaces and comes with pre-installed libraries such as NumPy, pandas, scikit-learn, Matplotlib, and more.
Details
- Author
- taiji1985
- Downloads
- 321
- Categories
- Other
Jump to
- Safe Python code execution in isolated namespaces
- Pre-installed data science and machine learning libraries
- Real-time capture of stdout, stderr, and return values
- Fully compatible with the Model Context Protocol
- Simple API: execute_python(code) returns a dict with output, error, and success
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Python Runner MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Run the server directly with uvx python-runner (no installation required) or install manually via uv/pip and run python main.py. For use with Claude Desktop, add the server configuration to your claude_desktop_config.json file.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"python runner mcp server": {
"python_runner_mcp": {
"command": "uvx",
"args": [
"python-runner"
]
}
}
}
}McpServers
{
"python_runner_mcp": {
"command": "uvx",
"args": [
"python-runner"
]
}
}Python Runner MCP Server
A Python code execution server based on the FastMCP framework, designed specifically for data science and machine learning workflows.
🚀 Features
- Safe Python Code Execution: Execute Python code in isolated namespaces
- Rich Data Science Libraries: Pre-installed with commonly used data science and machine learning packages
- Real-time Output Capture: Capture standard output, error output, and return values
- MCP Protocol Support: Fully compatible with Model Context Protocol
- Easy to Use: Provides a simple and clean API interface
⚡ Quick Start (Recommended)
Use uvx to run the server directly without installation: [TODO ..... ]
```bash
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