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MCP-Python-Executor
Ein Modellkontext -Protokollserver (MCP) zum Ausführen von Python -Code und Verwaltung von Python -Paketen.
3 years
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MCP Python Executor
A Model Context Protocol (MCP) server for executing Python code and managing Python packages.
Features
- Execute Python code with safety constraints
- Install and manage Python packages
- Pre-configure commonly used packages
- Resource monitoring and limits
- Health checks and metrics
- Structured logging
Configuration
The server can be configured through environment variables in the MCP settings:
{
"mcpServers": {
"mcp-python-executor": {
"command": "node",
"args": ["path/to/python-executor/build/index.js"],
"env": {
"PREINSTALLED_PACKAGES": "numpy pandas matplotlib scikit-learn",
"MAX_MEMORY_MB": "512",
"EXECUTION_TIMEOUT_MS": "30000",
"MAX_CONCURRENT_EXECUTIONS": "5",
"LOG_LEVEL": "info",
"LOG_FORMAT": "json"
}
}
}
}
Environment Variables
-
PREINSTALLED_PACKAGES
: Space-separated list of Python packages to install on startup -
MAX_MEMORY_MB
: Maximum memory limit per execution (default: 512) -
EXECUTION_TIMEOUT_MS
: Maximum execution time in milliseconds (default: 30000) -
MAX_CONCURRENT_EXECUTIONS
: Maximum number of concurrent executions (default: 5) -
LOG_LEVEL
: Logging level (debug|info|error, default: info) -
LOG_FORMAT
: Log format (json|text, default: json)
Available Tools
1. execute_python
Execute Python code and return the results.
interface ExecutePythonArgs {
code?: string; // Python code to execute (inline)
scriptPath?: string; // Path to existing Python script file (alternative to code)
inputData?: string[]; // Optional input data
}
Examples:
// Example with inline code
{
"code": "print('Hello, World!!')\nfor i in range(3): print(i)",
"inputData": ["optional", "input", "data"]
}
// Example with script path
{
"scriptPath": "/path/to/your_script.py",
"inputData": ["optional", "input", "data"]
}
2. install_packages
Install Python packages.
interface InstallPackagesArgs {
packages: string[];
}
Example:
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Reviews

user_YDymRl7D
I recently started using Awesome MCP Servers by habitoai, and I am thrilled with the performance and reliability it offers. The setup process was smooth, and the server response time is impressive. If you're looking for a powerful and efficient server solution, I highly recommend checking it out at https://mcp.so/server/awesome-mcp-servers/habitoai. You won't be disappointed!