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MCP Sandbox

@JohanLi233

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MCP Sandbox について

Python sandboxes for llms

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

基本情報

カテゴリ

推論

ライセンス

Apache-2.0

ランタイム

python

トランスポート

stdio

公開者

JohanLi233

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.

コメント

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