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RAG Config Generator MCP

RAG Config Generator MCP

by Bisma474
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

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

Related MCP server: RAG Factory

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

Endpoint

Description

GET /

Server info

GET /generate-rag-config?description=...

Generate full RAG config

GET /suggest-chunking?doc_type=...&doc_size=...

Chunking recommendations

GET /suggest-embeddings?use_case=...&budget=...

Embedding recommendations

GET /suggest-vector-store?data_size=...&latency=...

Vector store recommendations

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

Tool Schema Changelog

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