ai-network-engineer

# LLM Network Agent - Modular AI-Powered Network Configuration Agent An AI agent that acts as a **Network Engineer**, managing network infrastructure using a **modular architecture of MCP (Model Context Protocol) servers**. Add or remove MCP servers based on your specific needs. ## 🎯 What It Does Configure and manage network devices (Cisco routers, Linux hosts) in a GNS3 simulation environment using natural language commands through an AI agent. **Example:** "Change PC3's IP address to 10.0.0.15/24" → Agent allocates IP via IPAM → Updates inventory → Deploys config → Verifies connectivity ## 🏗️ Architecture 7 MCP servers working together: - **Librarian** - Source of truth (inventory.yaml) - **IPAM** - IP address management - **Verifier** - Pre-deployment validation - **Deployer** - Configuration deployment - **Observer** - Network monitoring - **Auditor** - Security compliance - **TrafficGen** - Traffic testing > [!IMPORTANT] > When changing the network topology in GNS3 (adding/removing devices or links), you must **manually modify** `shared/inventory.yaml` to match the new topology. ## 📋 Requirements - **Docker** (required) - **GNS3** simulation environment - **Cisco IOS router image** (for GNS3 - you need to provide this) - **Gemini CLI** or Claude Desktop (for AI integration) - **Node.js/npm** (for Gemini CLI) ## 🚀 Quick Start ### 1. Run Setup Script ```bash chmod +x setup.sh ./setup.sh ``` This script will: - ✅ Check Docker installation - ✅ Install Gemini CLI (if needed) - ✅ Build and start Docker containers - ✅ Generate Gemini settings with all MCP servers ### 2. Import GNS3 Project 1. Open GNS3 2. Import `Test_project.gns3project` 3. Ensure you have a **Cisco IOS router image** configured in GNS3 4. Start the topology ### 3. Configure AI Client **For Gemini:** The setup script automatically creates `~/.gemini/settings.json` with all MCP servers. **For Claude Desktop:** Copy MCP server configurations from generated settings to your Claude config: - Mac: `~/Library/Application Support/Claude/claude_desktop_config.json` - Windows: `%APPDATA%\Claude\claude_desktop_config.json` ### 4. Start Using ```bash gemini ``` **Important:** When the CLI starts, type **`@GEMINI.md`** to load the system prompt and agent rules. Try: *"Show me all devices in the network"* or *"Change PC1 IP to 192.168.1.10/24"* ## 🎥 Video Demonstration Check out `demonstration.mp4` for a complete walkthrough of the system in action. ## ⚠️ Troubleshooting **If MCP servers aren't working:** 1. **Check Gemini settings:** Make sure `~/.gemini/settings.json` has all 7 MCP servers configured 2. **Verify Docker:** Run `docker ps` and confirm `mcp-toolbox` container is running 3. **Restart Gemini:** Exit and restart the Gemini CLI 4. **Check logs:** Run `docker logs mcp-toolbox` **If setup.sh fails:** ```bash # Manually install Docker first sudo apt-get update && sudo apt-get install docker.io docker-compose # Then run setup.sh again ./setup.sh ``` ## 📚 Documentation - **GEMINI.md** - AI agent system prompt and workflow - **MCP_SERVERS_GUIDE.md** - Detailed guide for each MCP server ## 🏛️ Project Structure ``` . ├── servers/ # 7 MCP servers │ ├── librarian/ │ ├── ipam/ │ ├── deployer/ │ ├── verifier/ │ ├── observer/ │ ├── auditor/ │ └── traffic_gen/ ├── shared/ # Common utilities & inventory │ ├── inventory.yaml │ ├── gns3_utils.py │ └── topology_physical.yaml ├── setup.sh # Automated setup └── docker-compose.yml ``` ## 🤝 Contributing This project demonstrates AI-powered network automation. Feel free to extend it with additional MCP servers or integration with other network simulation platforms. ## 👥 Authors - **Abellache Rabah** - abellache.rabah@outlook.com - **Sabrina Sahouli** - sabrinasahouli2001@gmail.com ## 📄 License MIT License - See LICENSE file for details --- ## ⚠️ Disclaimer **This project is for educational and demonstration purposes only.** This is a simulation/demonstration project that has **NOT been tested in production environments** and is **NOT recommended for production use**. It is intended solely for learning, research, and demonstration of AI-powered network automation concepts.