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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

A comprehensive MCP server integrating OpenAI GPT models for AI-powered tasks like code analysis, generation, and translation, along with system utilities, Docker management, network diagnostics, and web tools.

README.md

Athena MCP Server

A comprehensive Model Context Protocol (MCP) server that provides AI-powered tools and system utilities. This server integrates with OpenAI GPT models to deliver intelligent responses and analysis capabilities.

Features

Core AI Tools (OpenAI GPT-powered)

  • ask_athena: Intelligent AI assistant for general queries and problem-solving
  • analyze_code: Advanced code analysis with optimization suggestions
  • generate_code: Intelligent code generation based on requirements
  • text_summarize: AI-powered text summarization with customizable length and style
  • translate_text: Multi-language translation using OpenAI models
  • image_generate: DALL-E powered image generation

System & Development Tools

  • get_system_stats: Real-time system monitoring (CPU, memory, disk usage)
  • file_operations: Comprehensive file and directory management
  • process_monitor: System process monitoring and management
  • docker_manage: Docker container and image management
  • network_tools: Network diagnostics (ping, port scan, DNS lookup, traceroute)

Web & API Tools

  • web_request: HTTP client for API testing and web scraping
  • weather_info: Real-time weather information using OpenWeatherMap API
  • github_operations: GitHub repository management and code search

📁 Project Structure

Athena MCP/
├── app.js                 # Backend entry point
├── mcp-server.js          # MCP server for Trae integration
├── mcp-config.json        # MCP configuration file
├── package.json           # Backend dependencies
├── .env                   # Environment variables
├── tools/                 # Custom tools directory
│   └── get_cpu_stats.js   # CPU statistics tool
├── frontend/              # React frontend
│   ├── package.json       # Frontend dependencies
│   ├── public/
│   └── src/
│       ├── App.js         # Main React component
│       ├── App.css        # Component styles
│       ├── index.js       # React entry point
│       └── index.css      # Global styles
├── docker-compose.yml     # Docker orchestration
├── Dockerfile.backend     # Backend Docker image
└── README.md             # This file

🔌 MCP Integration with Trae

Quick Setup for Trae

  1. Install dependencies:
   npm install
  1. Start MCP server:
   npm run mcp
  1. Add to Trae configuration:

Add this to your Trae MCP configuration: ``json { "mcpServers": { "athena": { "command": "node", "args": ["mcp-server.js"], "cwd": "d:\\Projects\\Athena MCP" } } } ``

Available MCP Tools

| Tool Name | Description | |-----------|-------------| | ask_athena | Ask Athena AI assistant questions and get intelligent responses powered by OpenAI GPT | | get_system_stats | Get detailed system CPU, memory, and performance statistics | | analyze_code | Analyze code snippets with AI-powered review, explain, optimize, or debug modes | | generate_code | Generate code based on requirements and specifications using OpenAI |

MCP Tool Examples

Ask Athena: ``json { "name": "ask_athena", "arguments": { "prompt": "How do I optimize React performance?", "context": "Working on a large React application with performance issues" } } ``

Get System Stats: ``json { "name": "get_system_stats", "arguments": { "detailed": true } } ``

Analyze Code: ``json { "name": "analyze_code", "arguments": { "code": "function fibonacci(n) { return n <= 1 ? n : fibonacci(n-1) + fibonacci(n-2); }", "language": "javascript", "analysis_type": "optimize" } } ``

🛠️ Setup & Installation

Prerequisites

  • Node.js 18+ and npm
  • (Optional) Docker and Docker Compose

Method 1: Local Development

  1. Clone and setup backend:
   cd "d:\Projects\Athena MCP"
   npm install
  1. Setup frontend:
   cd frontend
   npm install
  1. Configure environment:
  • Edit .env file and add your OpenAI API key:
   PORT=4000
   OPENAI_API_KEY=your_actual_api_key_here
  1. Run the applications:

Terminal 1 (Backend): ```bash npm start

Backend runs on http://localhost:4000

   
   **Terminal 2 (Frontend):**

cd frontend npm start

Frontend runs on http://localhost:3000


### Method 2: Docker Compose

1. **Set environment variables:**

Create .env file with your API key

echo "OPENAI_API_KEY=your_actual_api_key_here" > .env ```

  1. Run with Docker:
   docker-compose up --build

This will start:

  • Backend on http://localhost:4000
  • Frontend on http://localhost:3000

🔌 API Endpoints

Backend API (Port 4000)

| Method | Endpoint | Description | |--------|----------|-------------| | GET | / | API information and available endpoints | | POST | /ask | Send a prompt to Athena AI | | GET | /cpu | Get system CPU and memory statistics | | GET | /health| Health check endpoint |

Example API Usage

Ask Athena a question: ``bash curl -X POST http://localhost:4000/ask \ -H "Content-Type: application/json" \ -d '{"prompt": "What is artificial intelligence?"}' ``

Get CPU statistics: ``bash curl http://localhost:4000/cpu ``

🎨 Frontend Features

  • Modern UI: Clean, responsive design with gradient backgrounds
  • Real-time Interaction: Instant feedback and loading states
  • Error Handling: User-friendly error messages
  • Mobile Responsive: Works on all device sizes
  • System Monitoring: Visual display of CPU and memory stats

🔧 Development

Adding New Tools

  1. Create a new file in the tools/ directory:
   // tools/my_new_tool.js
   function myNewTool() {
     // Your tool logic here
     return { result: "Tool output" };
   }
   
   module.exports = { myNewTool };
  1. Import and use in app.js:
   const { myNewTool } = require('./tools/my_new_tool');
   
   app.get('/my-endpoint', (req, res) => {
     const result = myNewTool();
     res.json(result);
   });

Environment Variables

| Variable | Description | Default | |----------|-------------|---------| | PORT | Backend server port | 4000 | | OPENAI_API_KEY | OpenAI API key for AI features | Required | | NODE_ENV | Environment mode | development |

🐳 Docker Commands

# Build and run
docker-compose up --build

# Run in background
docker-compose up -d

# Stop services
docker-compose down

# View logs
docker-compose logs -f

# Rebuild specific service
docker-compose build backend
docker-compose build frontend

🚀 Production Deployment

  1. Set production environment variables
  2. Build optimized frontend:
   cd frontend
   npm run build
  1. Use process manager like PM2:
   npm install -g pm2
   pm2 start app.js --name athena-backend

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Test thoroughly
  5. Submit a pull request

📝 License

MIT License - feel free to use this project for your own purposes.

🆘 Troubleshooting

Backend won't start:

  • Check if port 4000 is available
  • Verify Node.js version (18+)
  • Check .env file configuration

Frontend can't connect to backend:

  • Ensure backend is running on port 4000
  • Check CORS configuration
  • Verify API_BASE_URL in frontend

Docker issues:

  • Ensure Docker is running
  • Check port conflicts
  • Verify environment variables in docker-compose.yml

---

Happy coding! 🎉

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