
MCP Python Interpreter
A Model Context Protocol server that allows LLMs to interact with Python environments, enabling code execution, file operations, package management, and development workflows.
Tools
read_file
Read the content of any file, with size limits for safety. Args: file_path: Path to the file (relative to working directory or absolute) max_size_kb: Maximum file size to read in KB (default: 1024) Returns: str: File content or an error message
write_file
Write content to a file in the working directory or system-wide if allowed. Args: file_path: Path to the file to write (relative to working directory or absolute if system access is enabled) content: Content to write to the file overwrite: Whether to overwrite the file if it exists (default: False) encoding: File encoding (default: utf-8) Returns: str: Status message about the file writing operation
list_directory
List all Python files in a directory or subdirectory. Args: directory_path: Path to directory (relative to working directory or absolute, empty for working directory)
list_python_environments
List all available Python environments (system Python and conda environments).
list_installed_packages
List installed packages for a specific Python environment. Args: environment: Name of the Python environment (default: default if custom path provided, otherwise system)
run_python_code
Execute Python code and return the result. Code runs in the working directory. Args: code: Python code to execute environment: Name of the Python environment to use (default if custom path provided, otherwise system) save_as: Optional filename to save the code before execution (useful for future reference)
install_package
Install a Python package in the specified environment. Args: package_name: Name of the package to install environment: Name of the Python environment (default if custom path provided, otherwise system) upgrade: Whether to upgrade the package if already installed (default: False)
write_python_file
Write content to a Python file in the working directory or system-wide if allowed. Args: file_path: Path to the file to write (relative to working directory or absolute if system access is enabled) content: Content to write to the file overwrite: Whether to overwrite the file if it exists (default: False)
run_python_file
Execute a Python file and return the result. Args: file_path: Path to the Python file to execute (relative to working directory or absolute if system access is enabled) environment: Name of the Python environment to use (default if custom path provided, otherwise system) arguments: List of command-line arguments to pass to the script
README
MCP Python Interpreter
A Model Context Protocol (MCP) server that allows LLMs to interact with Python environments, read and write files, execute Python code, and manage development workflows.
Features
- Environment Management: List and use different Python environments (system and conda)
- Code Execution: Run Python code or scripts in any available environment
- Package Management: List installed packages and install new ones
- File Operations:
- Read files of any type (text, source code, binary)
- Write text and binary files
- Python Prompts: Templates for common Python tasks like function creation and debugging
Installation
You can install the MCP Python Interpreter using pip:
pip install mcp-python-interpreter
Or with uv:
uv install mcp-python-interpreter
Usage with Claude Desktop
- Install Claude Desktop
- Open Claude Desktop, click on menu, then Settings
- Go to Developer tab and click "Edit Config"
- Add the following to your
claude_desktop_config.json
:
{
"mcpServers": {
"mcp-python-interpreter": {
"command": "uvx",
"args": [
"mcp-python-interpreter",
"--dir",
"/path/to/your/work/dir",
"--python-path",
"/path/to/your/python"
],
"env": {
"MCP_ALLOW_SYSTEM_ACCESS": 0
},
}
}
}
For Windows:
{
"mcpServers": {
"python-interpreter": {
"command": "uvx",
"args": [
"mcp-python-interpreter",
"--dir",
"C:\\path\\to\\your\\working\\directory",
"--python-path",
"/path/to/your/python"
],
"env": {
"MCP_ALLOW_SYSTEM_ACCESS": 0
}
}
}
}
- Restart Claude Desktop
- You should now see the MCP tools icon in the chat interface
The --dir
parameter is required and specifies where all files will be saved and executed. This helps maintain security by isolating the MCP server to a specific directory.
Prerequisites
- Make sure you have
uv
installed. If not, install it using:curl -LsSf https://astral.sh/uv/install.sh | sh
- For Windows:
powershell -ExecutionPolicy Bypass -Command "iwr -useb https://astral.sh/uv/install.ps1 | iex"
Available Tools
The Python Interpreter provides the following tools:
Environment and Package Management
- list_python_environments: List all available Python environments (system and conda)
- list_installed_packages: List packages installed in a specific environment
- install_package: Install a Python package in a specific environment
Code Execution
- run_python_code: Execute Python code in a specific environment
- run_python_file: Execute a Python file in a specific environment
File Operations
- read_file: Read contents of any file type, with size and safety limits
- Supports text files with syntax highlighting
- Displays hex representation for binary files
- write_file: Create or overwrite files with text or binary content
- write_python_file: Create or overwrite a Python file specifically
- list_directory: List Python files in a directory
Available Resources
- python://environments: List all available Python environments
- python://packages/{env_name}: List installed packages for a specific environment
- python://file/{file_path}: Get the content of a Python file
- python://directory/{directory_path}: List all Python files in a directory
Prompts
- python_function_template: Generate a template for a Python function
- refactor_python_code: Help refactor Python code
- debug_python_error: Help debug a Python error
Example Usage
Here are some examples of what you can ask Claude to do with this MCP server:
- "Show me all available Python environments on my system"
- "Run this Python code in my conda-base environment: print('Hello, world!')"
- "Create a new Python file called 'hello.py' with a function that says hello"
- "Read the contents of my 'data.json' file"
- "Write a new configuration file with these settings..."
- "List all packages installed in my system Python environment"
- "Install the requests package in my system Python environment"
- "Run data_analysis.py with these arguments: --input=data.csv --output=results.csv"
File Handling Capabilities
The MCP Python Interpreter now supports comprehensive file operations:
- Read text and binary files up to 1MB
- Write text and binary files
- Syntax highlighting for source code files
- Hex representation for binary files
- Strict file path security (only within the working directory)
Security Considerations
This MCP server has access to your Python environments and file system. Key security features include:
- Isolated working directory
- File size limits
- Prevented writes outside the working directory
- Explicit overwrite protection
Always be cautious about running code or file operations that you don't fully understand.
License
MIT
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