MCPHub LabRegistrycode-sandbox-mcp
Automata-Labs-team

code sandbox mcp

Built by Automata-Labs-team 316 stars

What is code sandbox mcp?

A high-performance MCP server implementation for code-sandbox-mcp that bridges the gap between the Model Context Protocol and external services. It allows Large Language Models to interact with your data and tools with low latency and native support.

How to use code sandbox mcp?

1. Ensure you have an MCP-compatible client (like Claude Desktop) installed. 2. Configure your server with: npx @modelcontextprotocol/code-sandbox-mcp 3. Restart your client and verify the new tools are available in the system catalog.
🛡️ Scoped (Restricted)
npx @modelcontextprotocol/code-sandbox-mcp --scope restricted
🔓 Unrestricted Access
npx @modelcontextprotocol/code-sandbox-mcp

Key Features

Native MCP Protocol Support
High-performance Data Streaming
Type-safe Tool Definitions
Seamless Environment Integration

Optimized Use Cases

Connecting external databases to AI workflows
Automating workflow tasks via natural language
Augmenting developer productivity with specialized tools

code sandbox mcp FAQ

Q

What is an MCP server?

MCP is an open standard that enables developers to build secure, two-way integrations between AI models and local or remote data sources.

Q

Is this server ready for production?

Yes, this server follows standard MCP security patterns and tool-restricted access.

Official Documentation

View on GitHub

Code Sandbox MCP 🐳

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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

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.

Global Ranking

7.1
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Manual Config

{ "mcpServers": { "code-sandbox-mcp": { "command": "npx", "args": ["code-sandbox-mcp"] } } }