Generative AI Knowledge Assistant

A comprehensive AI assistant that uses Model Context Protocol (MCP) to integrate multiple data sources, enabling complex queries and context-aware answers.

Features

• MCP Integration: Seamless integration with multiple data sources (files, databases, APIs)
• AI-Powered Processing: LLM-powered summarization and content generation
• Interactive Dashboard: React.js + Plotly/Dash visualization interface
• Context-Aware Queries: Intelligent query processing with multi-source context
• Real-time Analytics: User interaction metrics and query performance tracking

Project Structure

├── backend/                 # FastAPI backend
│   ├── api/                # API endpoints
│   ├── core/               # Core business logic
│   ├── models/             # Data models
│   └── services/           # Service layer
├── frontend/               # React.js dashboard
│   ├── src/
│   │   ├── components/     # React components
│   │   ├── pages/          # Dashboard pages
│   │   └── utils/          # Utility functions
├── mcp_server/             # MCP server implementation
│   ├── tools/              # MCP tools
│   └── integrations/       # Data source integrations
├── data/                   # Sample data and configurations
└── tests/                  # Test files

Quick Start

1. Install dependencies:

pip install -r requirements.txt

2. Set up environment variables:

cp .env.example .env
# Edit .env with your API keys and configurations

3. Start the MCP server:

python mcp_server/main.py

4. Start the backend API:

python backend/main.py

5. Start the frontend dashboard:

cd frontend && npm start

Configuration

• OpenAI API key for LLM functionality
• Database connections for data sources
• MCP server configurations
• Dashboard customization options

API Documentation

Once running, visit http://localhost:8000/docs for interactive API documentation.