iflow-mcp_philschmid-code-sandbox-mcp

# Code Sandbox MCP Server The Code Sandbox MCP Server is a lightweight, STDIO-based Model Context Protocol (MCP) Server, allowing AI assistants and LLM applications to safely execute code snippets using containerized environments. It is uses the [llm-sandbox](https://github.com/vndee/llm-sandbox) package to execute the code snippets.  **How It Works:** 1. Starts a container session (podman, docker, etc.) and ensures the session is open. 2. Writes the `code` to a temporary file on the host. 3. Copies this temporary file into the container at the configured `workdir`. 4. Executes the language-specific commands to run the code, e.g. python `python3 -u code.py` or javascript `node -u code.js` 5. Captures the output and error streams from the container. 6. Returns the output and error streams to the client. 7. Stops and removes the container. **Available Tools:** - **run_python_code** - Executes a snippet of Python code in a secure, isolated sandbox. - `code` (string, required): The Python code to execute. - **run_js_code** - Executes a snippet of JavaScript (Node.js) code in a secure, isolated sandbox. - `code` (string, required): The JavaScript code to execute. ## Installation ```bash pip install git+https://github.com/philschmid/code-sandbox-mcp.git ``` ## Getting Started: Usage with an MCP Client Examples: - [Local Client Python](./examples/test_local_client_python.py) example for running python code - [Gemini SDK](./examples/test_gemini.py) example for running python code with the Gemini SDK - [Calling Gemini from a client](./examples/test_client_gemini_call.py) example for running python code that uses the Gemini SDK and passes through the Gemini API key - [Local Client Javascript](./examples/test_local_client_js.py) example for running javascript code To use the Code Sandbox MCP server, you need to add it to your MCP client's configuration file (e.g., in your AI assistant's settings). The server is …