MCP Kafka Schema Reg

# Kafka Schema Registry MCP with LLama Integration This repository includes a complete local LLama integration demo for the Kafka Schema Registry MCP server. ## 🚀 Quick Start **All LLama integration files are organized in the `demo/` folder.** ```bash # Clone and navigate to demo git clone https://github.com/aywengo/kafka-schema-reg-mcp.git cd kafka-schema-reg-mcp/demo # Start the demo chmod +x run-llama-mcp.sh ./run-llama-mcp.sh start # Choose your interface: # Option A: CLI client python client-example.py # Option B: Use with VSCode (see setup below) ``` ## 📁 What's in the Demo Folder The `demo/` folder contains a complete working example of LLama integration: - **`docker-compose-llama.yml`** - Complete Docker setup with LLama, Kafka, Schema Registry - **`run-llama-mcp.sh`** - One-command setup and management script - **`client-example.py`** - Interactive CLI client for natural language queries - **`README.md`** - Complete documentation and usage guide - **Bridge service files** - Integration layer between LLama and MCP ## 🎯 What You Can Do Ask natural language questions about your Schema Registry: - "List all subjects in the schema registry" - "Show me the structure of the user-events schema" - "Check if this schema is compatible with the latest version" - "Export all schemas from the production context" ## 💻 Interface Options ### Option A: Interactive CLI Client ```bash python client-example.py ``` Perfect for quick queries and testing. ### Option B: VSCode Integration Use Schema Registry directly in your development workflow: 1. **Install MCP Extension**: Install "Claude Dev" or similar MCP-compatible extension 2. **Configure Connection**: Add to your VSCode `settings.json`: ```json { "claudeDev.mcpServers": { "kafka-schema-registry": { "command": "docker", "args": ["exec", "-i", "mcp-server", "python", "-m", "kafka_schema_registry_mcp.server"], "env": { "SCHEMA_REGISTRY_URL": "http://localhost:38081" } } } } ``` 3. **Start Chatting**: Use the extension chat to ask schema questions while coding ### Option C: Direct API ```bash curl -X POST http://localhost:8080/chat \ -H "Content-Type: application/json" \ -d '{"message": "List all subjects", "use_mcp": true}' ``` ## 🏗️ Architecture ``` Your Questions → LLama (Ollama) → MCP Bridge → Schema Registry MCP → Kafka Schema Registry ↑ ↓ └─────────────── Natural Language Responses ←─────────────────────────────┘ ``` ## 🔧 VSCode Benefits - 🔥 **Code Context**: Ask about schemas while viewing your code - 📝 **Documentation**: Generate schema docs directly in workspace - 🔄 **Workflow Integration**: Schema queries during development - 💡 **IntelliSense**: Schema-aware suggestions (with compatible extensions) ## 📖 Full Documentation See [`demo/README.md`](demo/README.md) for complete documentation, including: - Installation and setup instructions - VSCode configuration examples - Usage examples and commands - Configuration options - Troubleshooting guide - API reference ## 🔧 Core MCP Server This repository maintains full compatibility with the original MCP server functionality. The LLama integration is purely additive and runs alongside the existing server. ## 🚀 Getting Started 1. **Go to the demo folder**: `cd demo` 2. **Read the documentation**: `cat README.md` 3. **Start the demo**: `./run-llama-mcp.sh start` 4. **Choose your interface**: - **CLI**: `python client-example.py` - **VSCode**: Configure extension and chat in your editor - **API**: `curl http://localhost:8080/chat` --- **Ready to try it? Head to the [`demo/`](demo/) folder! 🎉**