MCP-RAG
by hulk-pham
This is a demo of a Retrieval-Augmented Generation (RAG) application integrated with an MCP server. It allows users to ask questions about a company using context-aware prompts and document retrieval.
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RAG Application
A demo of Retrieval-Augmented Generation (RAG) application with MCP server integration.
Screenshot
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