MCP Python Toolbox
by gianlucamazza
A Model Context Protocol (MCP) server that provides a comprehensive set of tools for Python development, enabling AI assistants like Claude to effectively work with Python code and projects. It allows Claude to perform Python development tasks through a standardized interface.
Last updated: N/A
What is MCP Python Toolbox?
MCP Python Toolbox is a Model Context Protocol server designed to provide AI assistants like Claude with the ability to perform Python development tasks. It offers a standardized interface for file operations, code analysis, project management, and code execution within a controlled environment.
How to use MCP Python Toolbox?
The toolbox can be used as a CLI tool, integrated with Claude Desktop, or programmatically. As a CLI tool, it can be started with a specified workspace. When integrated with Claude Desktop, it allows Claude to access Python development tools. Programmatically, it can be used by instantiating the PythonToolboxServer class and running it.
Key features of MCP Python Toolbox
Safe file operations within a workspace
Comprehensive code analysis (parsing, formatting, linting)
Virtual environment and dependency management
Controlled Python code execution
Integration with Claude Desktop
Use cases of MCP Python Toolbox
Enabling AI assistants to modify and manage Python projects
Automated code analysis and formatting
Dependency management and conflict resolution
Safe execution of Python code snippets
Building and testing Python applications in a controlled environment
FAQ from MCP Python Toolbox
What is the Model Context Protocol (MCP)?
What is the Model Context Protocol (MCP)?
MCP is a specification that defines a standardized interface for AI assistants to interact with development tools and environments.
How does the MCP Python Toolbox ensure code execution safety?
How does the MCP Python Toolbox ensure code execution safety?
The toolbox executes Python code in a controlled environment, utilizing the project's virtual environment and temporary file management to prevent unauthorized access or modifications.
What code formatting and linting tools are supported?
What code formatting and linting tools are supported?
The toolbox supports code formatting using Black (default) and PEP8 (using autopep8). It also provides comprehensive code linting using Pylint with detailed reports.
Can I manage dependencies from both requirements.txt and pyproject.toml?
Can I manage dependencies from both requirements.txt and pyproject.toml?
Yes, the toolbox supports dependency management from both requirements.txt and pyproject.toml files, offering flexibility in dependency management.
How do I contribute to the MCP Python Toolbox?
How do I contribute to the MCP Python Toolbox?
You contribute by forking the repository, creating a feature branch, committing your changes, pushing to the branch, then opening a pull request.