MCP Orchestration Server

# MCP Production Project Structure ## 📁 New Organized Structure ``` blackhole_mcp_production/ ├── 📂 core/ # Core MCP system │ ├── mcp_server.py # Main production server │ ├── mcp_client.py # Command-line client │ ├── conversation_engine.py # Conversational AI with MongoDB search │ ├── inter_agent_coordinator.py # Agent communication coordinator │ └── config.py # Configuration management │ ├── 📂 agents/ # Production agents directory │ ├── __init__.py # Agent discovery │ ├── base_agent.py # Base agent class │ ├── agent_manager.py # Agent lifecycle management │ │ │ ├── 📂 live_data/ # Live data agents │ │ ├── __init__.py │ │ ├── weather_agent.py # 🌤️ Live weather monitoring │ │ └── news_agent.py # 📰 Live news (future) │ │ │ ├── 📂 processing/ # Processing agents │ │ ├── __init__.py │ │ ├── math_agent.py # 🔢 Mathematical calculations │ │ ├── image_ocr_agent.py # 🖼️ Image text extraction │ │ ├── document_agent.py # 📄 Document analysis │ │ └── text_analyzer_agent.py # 📝 Text analysis (future) │ │ │ ├── 📂 communication/ # Communication agents │ │ ├── __init__.py │ │ ├── email_agent.py # 📧 Email automation │ │ ├── calendar_agent.py # 📅 Calendar management │ │ └── notification_agent.py # 🔔 Notifications (future) │ │ │ └── 📂 specialized/ # Specialized agents │ ├── __init__.py │ ├── workflow_agent.py # 🔄 Complex workflows │ └── search_agent.py # 🔍 Advanced search │ ├── 📂 database/ # Database management │ ├── __init__.py │ ├── mongodb_manager.py # MongoDB connection & operations │ ├── conversation_history.py # Chat history management │ ├── agent_logs.py # Agent activity logging │ ├── query_cache.py # Query caching system │ └── schemas/ # Database schemas │ ├── conversation_schema.py │ ├── agent_log_schema.py │ └── extracted_data_schema.py │ ├── 📂 storage/ # Data storage │ ├── 📂 agent_logs/ # Agent execution logs │ ├── 📂 conversation_history/ # Chat conversations │ ├── 📂 extracted_data/ # OCR & document extracts │ ├── 📂 uploaded_files/ # User uploaded files │ └── 📂 processed_outputs/ # Agent processing results │ ├── 📂 web_interface/ # Web interface │ ├── static/ # CSS, JS, images │ ├── templates/ # HTML templates │ └── app.py # Web application │ ├── 📂 tests/ # Testing suite │ ├── test_agents.py # Agent testing │ ├── test_database.py # Database testing │ └── test_integration.py # Integration testing │ ├── 📂 config/ # Configuration files │ ├── .env # Environment variables │ ├── agent_config.yaml # Agent configurations │ └── database_config.yaml # Database settings │ ├── 📂 scripts/ # Utility scripts │ ├── setup_project.py # Project setup │ ├── migrate_data.py # Data migration │ └── start_production.py # Production startup │ ├── 📂 docs/ # Documentation │ ├── API.md # API documentation │ ├── AGENTS.md # Agent documentation │ └── DEPLOYMENT.md # Deployment guide │ ├── requirements.txt # Dependencies ├── README.md # Project overview └── docker-compose.yml # Docker configuration ``` ## 🎯 Key Features ### 🤖 Agent Organization - **live_data/**: Real-time data agents (weather, news, etc.) - **processing/**: Data processing agents (math, OCR, documents) - **communication/**: Communication agents (email, calendar) - **specialized/**: Complex workflow and search agents ### 💾 MongoDB Integration - **Conversation History**: All user interactions stored - **Agent Logs**: Complete agent execution tracking - **Extracted Data**: OCR text, document analysis results - **Query Cache**: Fast retrieval of previous results ### 🔍 Intelligent Search - **MongoDB First**: Search existing data before calling agents - **Conversational AI**: Context-aware responses - **Inter-Agent Communication**: Agents collaborate for complex queries ### 📊 Data Flow 1. User query → MongoDB search first 2. If found → Conversational response 3. If not found → Route to appropriate agent(s) 4. Agent processing → Store results in MongoDB 5. Inter-agent communication for complex tasks 6. Final response to user