mcp-code-executor-server

## MCP Code Executor Server A robust **Model Context Protocol (MCP)** server that enables AI agents to execute code across multiple programming languages in a secure, isolated environment. --- ## 🚀 Overview MCP Code Executor Server standardizes how AI models connect to various programming runtimes by exposing a unified MCP tool endpoint. It allows AI assistants to: 1. **Submit** code in a supported language. 2. **Execute** it in a controlled, sandboxed environment. 3. **Receive** output, including compilation or runtime errors. --- ## 🔑 Key Features * **Multi-Language Support**: Java, Python, JavaScript, TypeScript, and C++. * **Secure Execution**: Isolated containers with resource limits (CPU, memory, timeouts). * **MCP Integration**: Conformant MCP server for seamless client discovery. * **Automatic Compilation**: Handles compile-and-run for Java, C++, and TypeScript. * **Detailed Error Feedback**: Returns both compile-time and runtime error messages. * **Resource Cleanup**: Automatically deletes temporary files and enforces execution timeouts. --- ## 📐 Architecture The MCP Code Executor Server follows a client-server model: * **MCP Client**: Protocol client that connects to this server. * **MCP Server**: This application, exposing code-execution tools. * **Sandboxed Runtimes**: Containers or isolated processes per request.  --- ## 🏁 Getting Started ### Prerequisites * **Java 17+** * **Python 3.8+** * **Node.js & npm** * **g++** or another C++ compiler ### Local Setup 1. **Clone the repository**: ```bash git clone https://github.com/yourusername/mcp-code-executor-server.git cd mcp-code-executor-server ``` 2. **Build & Run**: ```bash # Build the project ./mvnw clean package # Start the server ./mvnw spring-boot:run ``` The server listens on port **8080** by default. ### Using Docker For isolation, run in Docker: ```bash # Build Docker image docker build -t mcp-code-executor . # Run container docker run -p 8080:8080 mcp-code-executor ``` Or with Docker Compose: ```bash docker-compose up -d ``` --- ## 🛠️ Connecting MCP Clients 1. Start your MCP-compatible AI client. 2. Point it to `http://localhost:8080`. 3. Discover and invoke the `code-execution` tool. Example MCP request: ```json { "language": "python", "code": "print('Hello, world!')\nprint('hello again')" } ``` --- ## 🤝 Contributing Contributions are welcome!. --- ## 📄 License Apache License 2.0. See the [LICENSE](LICENSE) file for details.