# 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
