AI Customer Support Bot - MCP Server

# 🤖 AI Customer Support Bot - MCP Server <div align="center">      *A modern, extensible MCP server framework for building AI-powered customer support systems* [Features](#-features) • [Quick Start](#-quick-start) • [API Reference](#-api-reference) • [Architecture](#-architecture) • [Contributing](#-contributing) </div> --- ## 🌟 Overview A **Model Context Protocol (MCP)** compliant server framework built with modern Python. Designed for developers who want to create intelligent customer support systems without vendor lock-in. Clean architecture, battle-tested patterns, and ready for any AI provider. ```mermaid graph TB Client[HTTP Client] --> API[API Server] API --> MW[Middleware Layer] MW --> SVC[Service Layer] SVC --> CTX[Context Manager] SVC --> AI[AI Integration] SVC --> DAL[Data Access Layer] DAL --> DB[(PostgreSQL)] ``` ## ✨ Features <table> <tr> <td> 🏗️ **Clean Architecture** Layered design with clear separation of concerns 📡 **MCP Compliant** Full Model Context Protocol implementation </td> <td> 🔒 **Production Ready** Auth, rate limiting, monitoring included 🚀 **High Performance** Built on FastAPI with async support </td> </tr> <tr> <td> 🔌 **AI Agnostic** Integrate any AI provider easily 📊 **Health Monitoring** Comprehensive metrics and diagnostics </td> <td> 🛡️ **Secure by Default** Token auth and input validation 📦 **Batch Processing** Handle multiple queries efficiently </td> </tr> </table> ## 🚀 Quick Start ### Prerequisites - Python 3.8+ - PostgreSQL - Your favorite AI service (OpenAI, Anthropic, etc.) ### Installation ```bash # Clone and setup git clone https://github.com/ChiragPatankar/AI-Customer-Support-Bot--MCP-Server.git cd AI-Customer-Support-Bot--MCP-Server # Create virtual environment python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate # Install dependencies pip install -r requirements.txt # Setup environment cp .env.example .env # Edit .env with your configuration ``` ### Configuration ```bash # .env file DATABASE_URL=postgresql://user:password@localhost/customer_support_bot SECRET_KEY=your-super-secret-key RATE_LIMIT_REQUESTS=100 RATE_LIMIT_PERIOD=60 ``` ### Run ```bash # Setup database createdb customer_support_bot # Start server python app.py # 🚀 Server running at http://localhost:8000 ``` ## 📡 API Reference <details> <summary><strong>Core Endpoints</strong></summary> ### Health Check ```http GET /mcp/health ``` ### Process Single Query ```http POST /mcp/process Content-Type: application/json X-MCP-Auth: your-token X-MCP-Version: 1.0 { "query": "How do I reset my password?", "priority": "high" } ``` ### Batch Processing ```http POST /mcp/batch Content-Type: application/json X-MCP-Auth: your-token { "queries": [ "How do I reset my password?", "What are your business hours?" ] } ``` </details> <details> <summary><strong>Response Format</strong></summary> ### Success Response ```json { "status": "success", "data": { "response": "Generated AI response", "confidence": 0.95, "processing_time": "120ms" }, "meta": { "request_id": "req_123456", "timestamp": "2024-02-14T12:00:00Z" } } ``` ### Error Response ```json { "code": "RATE_LIMIT_EXCEEDED", "message": "Rate limit exceeded", "details": { "retry_after": 60, "timestamp": "2024-02-14T12:00:00Z" } } ``` </details> ## 🏗️ Architecture ### Project Structure ``` 📦 AI-Customer-Support-Bot--MCP-Server ├── 🚀 app.py # FastAPI application ├── 🗄️ database.py # Database configuration ├── 🛡️ middleware.py # Auth & rate limiting ├── 📋 models.py # ORM models ├── ⚙️ mcp_config.py # MCP protocol config ├── 📄 requirements.txt # Dependencies └── 📝 .env.example # Environment template ``` ### Layer Responsibilities | Layer | Purpose | Components | |-------|---------|------------| | **API** | HTTP endpoints, validation | FastAPI routes, Pydantic models | | **Middleware** | Auth, rate limiting, logging | Token validation, request throttling | | **Service** | Business logic, AI integration | Context management, AI orchestration | | **Data** | Persistence, models | PostgreSQL, SQLAlchemy ORM | ## 🔌 Extending with AI Services ### Add Your AI Provider 1. **Install your AI SDK:** ```bash pip install openai # or anthropic, cohere, etc. ``` 2. **Configure environment:** ```bash # Add to .env AI_SERVICE_API_KEY=sk-your-api-key AI_SERVICE_MODEL=gpt-4 ``` 3. **Implement service integration:** ```python # In service layer class AIService: async def generate_response(self, query: str, context: dict) -> str: # Your AI integration here return ai_response ``` ## 🔧 Development ### Running Tests ```bash pytest tests/ ``` ### Code Quality ```bash # Format code black . # Lint flake8 # Type checking mypy . ``` ### Docker Support ```dockerfile # Coming soon - Docker containerization ``` ## 📊 Monitoring & Observability ### Health Metrics - ✅ Service uptime - 🔗 Database connectivity - 📈 Request rates - ⏱️ Response times - 💾 Memory usage ### Logging ```python # Structured logging included { "timestamp": "2024-02-14T12:00:00Z", "level": "INFO", "message": "Query processed", "request_id": "req_123456", "processing_time": 120 } ``` ## 🔒 Security ### Built-in Security Features - 🔐 **Token Authentication** - Secure API access - 🛡️ **Rate Limiting** - DoS protection - ✅ **Input Validation** - SQL injection prevention - 📝 **Audit Logging** - Request tracking - 🔒 **Environment Secrets** - Secure config management ## 🚀 Deployment ### Environment Setup ```bash # Production environment variables DATABASE_URL=postgresql://prod-user:password@prod-host/db RATE_LIMIT_REQUESTS=1000 LOG_LEVEL=WARNING ``` ### Scaling Considerations - Use connection pooling for database - Implement Redis for rate limiting in multi-instance setups - Add load balancer for high availability - Monitor with Prometheus/Grafana ## 🤝 Contributing We love contributions! Here's how to get started: ### Development Setup ```bash # Fork the repo, then: git clone https://github.com/your-username/AI-Customer-Support-Bot--MCP-Server.git cd AI-Customer-Support-Bot--MCP-Server # Create feature branch git checkout -b feature/amazing-feature # Make your changes # ... # Test your changes pytest # Submit PR ``` ### Contribution Guidelines - 📝 Write tests for new features - 📚 Update documentation - 🎨 Follow existing code style - ✅ Ensure CI passes [](https://mseep.ai/app/chiragpatankar-ai-customer-support-bot-mcp-server) ## 📄 License This project is licensed under the **MIT License** - see the [LICENSE](LICENSE) file for details. --- <div align="center"> **Built with ❤️ by [Chirag Patankar](https://github.com/ChiragPatankar)** ⭐ **Star this repo if you find it helpful!** ⭐ [Report Bug](https://github.com/ChiragPatankar/AI-Customer-Support-Bot--MCP-Server/issues) • [Request Feature](https://github.com/ChiragPatankar/AI-Customer-Support-Bot--MCP-Server/issues) • [Documentation](https://github.com/ChiragPatankar/AI-Customer-Support-Bot--MCP-Server/wiki) </div>