
MCP Python Interpreter
A Model Context Protocol server that allows LLMs to interact with Python environments, execute code, and manage files within a specified working directory.
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
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.