RAG Application

A demo of Retrieval-Augmented Generation (RAG) application with MCP server integration.

Features

• MCP server integration
• Document retrieval using vector search with ChromaDB
• Context-aware prompt generation
• Integration with LLM APIs

Installation

pip install -r requirements.txt

Usage

Connect to the MCP server with Claude Desktop, Cursor, or your preferred IDE.

Use the process_query tool to ask questions about the company.

Configuration

Set up your environment variables in .env:

OPENAI_API_KEY=your_api_key

Project Structure

app/retrieval.py: Document retrieval functionality app/context.py: Context management app/llm_client.py: LLM API integration app/prompt_builder.py: Prompt construction

License

MIT