MCP Sandbox

Name: MCP Sandbox
Author: JohanLi233

@JohanLi233

Repository Homepage

About MCP Sandbox

Python sandboxes for llms

#python #mcp #sandbox #uv #llm #mcp-server

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-sandbox": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP Sandbox?

MCP Sandbox is a Python MCP server that enables users and LLMs to safely execute Python code and install packages in isolated Docker containers. It is designed for developers who need a secure, interactive Python runtime accessible via the Model Context Protocol.

How to use MCP Sandbox?

Clone the repository, install dependencies using uv venv and uv sync, then start the server with uv run main.py. Configuration (host, port, PyPI mirror) can be customized in config.toml. The default SSE endpoint is http://127.0.0.1:8181/sse. For Claude Desktop, configure via supergateway pointing to the SSE URL, optionally including an API key if authentication is enabled.

Key features of MCP Sandbox

Docker isolation for secure code execution
Package management with custom PyPI mirrors
File generation with web link access
Optional API key authentication
Built-in web UI for managing sandboxes
SSE support for real-time MCP integration

Use cases of MCP Sandbox

Running untrusted Python code in a secure sandbox
Installing and testing Python packages interactively
Generating visualizations (e.g., matplotlib plots) and saving them as files
Creating data files (CSV, Excel) accessible via HTTP links
Providing a safe Python runtime for LLM agents to execute code

FAQ from MCP Sandbox

What dependencies does MCP Sandbox require?

Python 3.12+, the uv package manager, and Docker.

How does MCP Sandbox communicate with clients?

It uses Server-Sent Events (SSE) for real-time communication; the default endpoint is http://127.0.0.1:8181/sse.

Where is executed code data stored?

Code runs in isolated Docker containers; generated files are stored in the results/ directory and made accessible via direct HTTP links.

Is authentication supported?

Yes, optional API key-based authentication can be enabled for multi-user environments.

What tools does MCP Sandbox provide?

Tools include create_sandbox, list_sandboxes, execute_python_code, install_package_in_sandbox, check_package_installation_status, execute_terminal_command, and upload_file_to_sandbox.

Comments

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