Safe Code Execution for Your AI Workflows

Skip the headache of setting up secure code execution environments. This MCP server gives your AI tools the ability to run code safely in isolated Docker containers—no complex sandboxing setup required.

The Problem with Code Execution in AI Tools

You want your AI assistant to run code snippets, test algorithms, or validate solutions. But executing arbitrary code is risky, and building secure execution environments from scratch is time-consuming. Most developers end up either:

• Copying code to separate environments manually (slow and annoying)
• Running code directly on their machine (security nightmare)
• Building custom Docker workflows (reinventing the wheel)

What You Get

Instant Docker-Isolated Execution: Every code snippet runs in a fresh container that gets destroyed after execution. Your system stays clean and secure.

Native MCP Integration: Works seamlessly with Claude Desktop, Cline, and other MCP-compatible AI tools. Your assistant can execute code and get results without you lifting a finger.

Zero-Config Security: Docker handles the isolation. No complex permission systems, chroot jails, or custom security policies to configure.

Real-World Use Cases

Algorithm Testing: Your AI writes a sorting algorithm? It can immediately test it with sample data and show you the results.

Data Processing Scripts: Working on data analysis? Let your AI run pandas operations and return processed results directly in the conversation.

Code Validation: Debugging a complex function? Your AI can execute test cases and verify the logic works as expected.

Learning and Experimentation: Exploring new programming concepts? Your AI can run examples and show you the output in real-time.

Quick Integration

1. Clone and setup:

   git clone https://github.com/axliupore/mcp-code-runner.git
   cd mcp-code-runner
   npm install
   

2. Add to your MCP client (Claude Desktop config):

   {
     "mcpServers": {
       "code-runner": {
         "command": "node",
         "args": ["path/to/mcp-code-runner/dist/index.js"]
       }
     }
   }
   

3. Start executing: Your AI can now run code snippets and return results directly in your conversations.

The server handles Docker container lifecycle, execution timeouts, and result capture automatically. You focus on the code, not the infrastructure.

Requirements: Docker running locally, Node.js 18+. That's it.

Ready to give your AI tools the ability to execute code safely? This MCP server makes it trivial to add secure code execution to any MCP-compatible workflow.