mcp_docker_python_interpreter

MCP Python Interpeter with Docker

Fork of this project which was modified to run inside Docker container.

Prerequisites

• Docker installed on your system

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

Run the Docker container

docker compose up -d

This will start the MCP server inside a Docker container and expose it on port 8050. All neccessary data are stored in the data folder.

Once the server is running, you can run the simple client in a separate terminal to test that server is running:

python client.py

The client will connect to the server and list available tools, list files in the data directory and read test.py file.

Stop the Docker container

docker compose down

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 (by default it's data 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 LLM 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)