RAG Config Generator MCP

An MCP (Model Context Protocol) server that generates RAG (Retrieval-Augmented Generation) pipeline configurations based on natural language descriptions.

Live Demo

• UI: Hugging Face Spaces

• API: Vercel Deployment

Features

• Generate Full Config: Describe your RAG use case in natural language

• Chunking Strategy: Get chunking recommendations based on document type

• Embeddings: Get embedding model recommendations based on use case and budget

• Vector Store: Get vector store recommendations based on data size and latency

API Endpoints

Installation

pip install -r requirements.txt

Usage

Run Gradio UI

python app.py

Opens at http://localhost:7860

Run MCP Server

python server.py

The MCP server will be available at http://localhost:8000/mcp

Project Structure

mcp/
├── server.py           # FastAPI + MCP server
├── rag_configs.py      # RAG config templates and logic
├── app.py              # Gradio UI
├── api/
│   └── index.py        # Vercel serverless function
├── requirements.txt    # Python dependencies
├── vercel.json         # Vercel configuration
└── README.md           # Documentation

Tech Stack

• Backend: Python, FastAPI, FastAPI-MCP

• Frontend: Gradio, HTML/CSS/JS

• Deployment: Vercel (API), Hugging Face Spaces (UI)

License

MIT