code-sandbox-mcp

What is Code Sandbox MCP?

Code Sandbox MCP is an MCP (Multi-Container Platform) server designed to create a secure and isolated environment for executing code within Docker containers. It provides AI applications with a safe space to run code while maintaining security through containerization.

How to use Code Sandbox MCP?

Installation

Prerequisites: Docker must be installed and running.

Quick Install (Linux, macOS):

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

Quick Install (Windows - PowerShell):

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

The installer will check for Docker, download the binary, and create configuration files.

Manual Installation:

1. Download the latest release for your platform from the releases page.
2. Place the binary in a directory within your system's PATH.
3. Make it executable (Unix-like systems only): chmod +x code-sandbox-mcp

Configuration

For Claude Desktop, the installer handles configuration. For other AI applications, configure them to use the code-sandbox-mcp binary as their code execution backend.

Available Tools

Code Sandbox MCP provides several tools for interacting with the sandboxed environment:

• sandbox_initialize: Initializes a new compute environment (Docker container).
• copy_project: Copies a directory to the sandboxed filesystem.
• write_file: Writes a file to the sandboxed filesystem.
• sandbox_exec: Executes commands within the sandboxed environment.
• copy_file: Copies a single file to the sandboxed filesystem.
• sandbox_stop: Stops and removes a running container sandbox.

Key Features of Code Sandbox MCP

• 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.
• Security Features: Isolated execution environment, resource limitations, and separate stdout/stderr streams.

Use Cases of Code Sandbox MCP

• AI Application Integration: Provides a secure and isolated environment for AI applications to execute code.
• Secure Code Execution: Safely run untrusted or potentially malicious code without affecting the host system.
• Development and Testing: Create consistent and reproducible environments for developing and testing code.
• Containerized Workflows: Leverage Docker for managing and executing code in a controlled manner.

FAQ about Code Sandbox MCP

• What are the prerequisites for Code Sandbox MCP? Docker must be installed and running on your system.

• Can I use my own Docker images? Yes, Code Sandbox MCP supports using any Docker image as your execution environment.

• How does Code Sandbox MCP ensure security? It uses Docker containers for isolated execution, applies resource limitations, and separates stdout/stderr streams to enhance security.

• Is Code Sandbox MCP cross-platform? Yes, it supports Linux, macOS, and Windows.

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 to stop and remove

Description: Gracefully stops the specified container with a 10-second timeout and removes it along with its volumes.

Container Logs Resource

A dynamic resource that provides access to container logs.

Resource Path: containers://{id}/logs
MIME Type: text/plain
Description: Returns all container logs from the specified container as a single text resource.

🔐 Security Features

• Isolated execution environment using Docker containers
• Resource limitations through Docker container constraints
• Separate stdout and stderr streams

🔧 Configuration

Claude Desktop

The installer automatically creates the configuration file. If you need to manually configure it:

Linux

// ~/.config/Claude/claude_desktop_config.json
{
    "mcpServers": {
        "code-sandbox-mcp": {
            "command": "/path/to/code-sandbox-mcp",
            "args": [],
            "env": {}
        }
    }
}

macOS

// ~/Library/Application Support/Claude/claude_desktop_config.json
{
    "mcpServers": {
        "code-sandbox-mcp": {
            "command": "/path/to/code-sandbox-mcp",
            "args": [],
            "env": {}
        }
    }
}

Windows

// %APPDATA%\Claude\claude_desktop_config.json
{
    "mcpServers": {
        "code-sandbox-mcp": {
            "command": "C:\\path\\to\\code-sandbox-mcp.exe",
            "args": [],
            "env": {}
        }
    }
}

Other AI Applications

For other AI applications that support MCP servers, configure them to use the code-sandbox-mcp binary as their code execution backend.

🛠️ Development

If you want to build the project locally or contribute to its development, see DEVELOPMENT.md.

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.