Code Sandbox MCP 🐳

A secure sandbox environment for executing code within Docker containers. This MCP server provides AI applications with a safe and isolated environment for running code while maintaining security through containerization.

🌟 Features

• Flexible Container Management: Create and manage isolated Docker containers for code execution
• Custom Environment Support: Use any Docker image as your execution environment
• File Operations: Easy file and directory transfer between host and containers
• Command Execution: Run any shell commands within the containerized environment
• Real-time Logging: Stream container logs and command output in real-time
• Auto-Updates: Built-in update checking and automatic binary updates
• Multi-Platform: Supports Linux, macOS, and Windows

🚀 Installation

Prerequisites

• Docker installed and running
  • Install Docker for Linux
  • Install Docker Desktop for macOS
  • Install Docker Desktop for Windows

Quick Install

Linux, MacOS

curl -fsSL https://raw.githubusercontent.com/Automata-Labs-team/code-sandbox-mcp/main/install.sh | bash

Windows

# Run in PowerShell
irm https://raw.githubusercontent.com/Automata-Labs-team/code-sandbox-mcp/main/install.ps1 | iex

The installer will:

1. Check for Docker installation
2. Download the appropriate binary for your system
3. Create necessary configuration files

Manual Installation

1. Download the latest release for your platform from the releases page
2. Place the binary in a directory in your PATH
3. Make it executable (Unix-like systems only):

   chmod +x code-sandbox-mcp
   

🛠️ Available Tools

sandbox_initialize

Initialize a new compute environment for code execution. Creates a container based on the specified Docker image.

Parameters:

• image (string, optional): Docker image to use as the base environment
  • Default: 'python:3.12-slim-bookworm'

Returns:

• container_id that can be used with other tools to interact with this environment

copy_project

Copy a directory to the sandboxed filesystem.

Parameters:

• container_id (string, required): ID of the container returned from the initialize call
• local_src_dir (string, required): Path to a directory in the local file system
• dest_dir (string, optional): Path to save the src directory in the sandbox environment

write_file

Write a file to the sandboxed filesystem.

Parameters:

• container_id (string, required): ID of the container returned from the initialize call
• file_name (string, required): Name of the file to create
• file_contents (string, required): Contents to write to the file
• dest_dir (string, optional): Directory to create the file in (Default: ${WORKDIR})

sandbox_exec

Execute commands in the sandboxed environment.

Parameters:

• container_id (string, required): ID of the container returned from the initialize call
• commands (array, required): List of command(s) to run in the sandboxed environment
  • Example: ["apt-get update", "pip install numpy", "python script.py"]

copy_file

Copy a single file to the sandboxed filesystem.

Parameters:

• container_id (string, required): ID of the container returned from the initialize call
• local_src_file (string, required): Path to a file in the local file system
• dest_path (string, optional): Path to save the file in the sandbox environment

sandbox_stop

Stop and remove a running container sandbox.

Parameters:

• container_id (string, required): ID of the container

... View full README on GitHub