MCP Document Processor

# MCP Document Processor An intelligent document processing system that uses the Model Context Protocol (MCP) to extract, analyze, and route business documents automatically. ## Overview The MCP Document Processor is a full-stack application (FastAPI backend + React frontend) that automates document processing workflows. The system classifies documents, extracts relevant information, and provides a user-friendly interface for document management. ## How MCP Works The Model Context Protocol (MCP) is the core framework that powers this document processor. Here's how it works in simple terms: 1. **Document Context**: When a document is uploaded, MCP creates a "context" object that acts as a container for: - The original document text - Document metadata (filename, upload time, etc.) - Processing history log - Extracted information with confidence scores 2. **Memory System**: These context objects are stored in a persistent memory system (file-based storage), allowing them to survive between API calls and server restarts. 3. **Smart Routing**: The system examines each document and routes it to the appropriate specialized processor: ``` Document → Router → Invoice/Contract/Email/Default Processor ``` 4. **Processing Pipeline**: Each document follows this workflow: ``` Upload → Classification → Information Extraction → Storage → Viewing ``` 5. **History & Confidence Tracking**: Every processing step is recorded with timestamps and confidence scores, providing full transparency into how information was extracted. ### Key Features - **Document Classification**: Automatically identifies document types (invoices, contracts, emails) - **Information Extraction**: Extracts key data using ML models with confidence scoring - **Persistent Storage**: File-based document storage that persists between server restarts - **Processing Pipeline**: Specialized processors for different document types - **Modern UI**: React-based dashboard for document upload, viewing, and management ## Architecture ### Backend - **Context System**: `MCPContext` objects maintain document state throughout processing - **Memory System**: Configurable storage (in-memory or file-based) with TTL management - **Processor Router**: Routes documents to specialized processors based on content - **Document Processors**: Type-specific processors with a default fallback processor - **ML Models**: Mock implementations of entity extraction, classification, and summarization ### Frontend - **Dashboard**: Document statistics and listing with filtering options - **Document View**: Detailed view of processed documents and extracted data - **Upload Interface**: Simple drag-and-drop document upload ## Setup ### Backend ```bash # Create and activate virtual environment python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate # Install dependencies pip install -r requirements.txt # Start server python app.py # Runs on http://localhost:8000 ``` ### Frontend ```bash # Navigate to frontend directory cd frontend # Install dependencies npm install # Start development server npm start # Runs on http://localhost:3000 ``` ## API Endpoints - `POST /api/documents/upload`: Upload a new document - `POST /api/documents/{document_id}/process`: Process a document - `GET /api/documents/{document_id}`: Get document details - `GET /api/documents`: List all documents - `DELETE /api/documents/{document_id}`: Delete a document - `GET /api/memory-status`: Check memory store status (debugging) # UI Features - **Dashboard**: Document statistics and listing with filtering options  - **Upload Interface**: Simple drag-and-drop document upload  - **Document View**: Detailed view of processed documents and extracted data  ## Technical Notes - Documents are stored in `data/documents/` with a 24-hour TTL - The DefaultProcessor handles any document type that specialized processors cannot handle - CORS is enabled to allow frontend-backend communication - Proxy is configured in package.json to route API requests during development