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.

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🚀 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.

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🔑 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.

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📐 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.

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🏁 Getting Started

Prerequisites

• Java 17+
• Python 3.8+
• Node.js & npm
• g++ or another C++ compiler

Local Setup

1. Clone the repository:

   git clone https://github.com/yourusername/mcp-code-executor-server.git
   cd mcp-code-executor-server

2. Build & Run:

   # 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:

# Build Docker image
docker build -t mcp-code-executor .

# Run container
docker run -p 8080:8080 mcp-code-executor

Or with Docker Compose:

docker-compose up -d

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🛠️ 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:

{
  "language": "python",
  "code": "print('Hello, world!')\nprint('hello again')"
}

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🤝 Contributing

Contributions are welcome!.

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📄 License

Apache License 2.0. See the LICENSE file for details.