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yzfly

MCP Python Interpreter

by yzfly
README.md
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# 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:

```bash
pip install mcp-python-interpreter
```

Or with uv:

```bash
uv install mcp-python-interpreter
```

## Usage with Claude Desktop

1. Install [Claude Desktop](https://claude.ai/download)
2. Open Claude Desktop, click on menu, then Settings
3. Go to Developer tab and click "Edit Config"
4. Add the following to your `claude_desktop_config.json`:

```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:

```json
{
  "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"
        },
    }
  }
}
```

5. Restart Claude Desktop
6. 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:
  ```bash
  curl -LsSf https://astral.sh/uv/install.sh | sh
  ```
- For Windows:
  ```powershell
  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

TDQS

A3.5/5.0

Scored across 10 tools

Disambiguation4/5

Most tools have distinct purposes, but there is some overlap between run_python_code and run_python_file that could cause confusion. The descriptions clarify that run_python_code handles code strings with multiple execution modes, while run_python_file executes existing files via subprocess, but both essentially execute Python code. Other tools like list_directory, read_file, and write_file are clearly distinct.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case, such as clear_session, install_package, list_directory, etc. There are no deviations in naming conventions, making the set predictable and easy to understand.

Tool Count5/5

With 10 tools, the count is well-scoped for a Python interpreter server. It covers key operations like code execution, file management, package installation, and session handling without being overwhelming or insufficient for the domain.

Completeness4/5

The tool set provides comprehensive coverage for Python development tasks, including code execution, file operations, package management, and session control. Minor gaps exist, such as no explicit tool for deleting files or uninstalling packages, but agents can work around these using existing tools like write_file with overwrite or other methods.

Maintenance

ActivityInactive
ResponsivenessSlow