Universal RAG MCP
Enables persistent, searchable memory for AI assistants across platforms like Claude, ChatGPT, and Gemini, using semantic search and automatic deduplication.
README
Universal RAG MCP
🧠 Intelligent cross-platform memory system for AI assistants
Give your AI assistants persistent, searchable memory that works across Claude, ChatGPT, Gemini, and more.
✨ Features
- 🧠 Smart Memory - Intelligent chunking filters noise, keeps only important information
- 🔍 Semantic Search - Find information by meaning, not just keywords
- 🚫 Auto-Deduplication - Tracks mention count instead of saving duplicates
- 🌐 Cross-Platform - Same memory across Claude, ChatGPT, Gemini, Cursor, Kiro
- ⚡ Fast - Sub-100ms searches with in-memory caching
- 🎯 Accurate - Multi-question support with parallel searches
- 🔒 Your Data - Stored in your Firebase/Pinecone accounts
Features
- Cross-platform: Same memory in Claude Desktop, ChatGPT, Gemini, and more
- Your data: You control it - stored in your Firebase/Pinecone accounts
- Zero config: 5-minute setup wizard handles everything
- Smart search: Semantic search with automatic reranking
- Fast: In-memory cache + hot/warm/cold storage tiers
🚀 Quick Start
# 1. Install
npm install -g @sid7vish/universal-rag-mcp
# 2. Setup (5 minutes)
universal-rag-mcp init
# 3. Add MCP config to your AI platform (shown at end of setup)
# 4. Restart your AI platform and test!
That's it! Your AI now has persistent memory.
📖 Documentation
Everything you need:
- Detailed setup instructions
- API keys walkthrough
- Platform configuration
- Troubleshooting
- Advanced usage
💬 Example Usage
You: Remember that I love TypeScript and I'm building SLAM v3
AI: Got it!
You: What am I working on?
AI: You're building SLAM v3 and you love TypeScript!
🏗️ Architecture
AI Platform (Claude/ChatGPT/Gemini)
↓ MCP Protocol
universal-rag-mcp
↓
Firebase (data) + Pinecone (vectors) + Voyage AI (embeddings)
🔑 What You Need
4 Free API Keys (setup wizard guides you):
- Firebase - Database storage (free: 1GB)
- Pinecone - Vector search (free: 5M vectors)
- Voyage AI - Primary embeddings (free: 10M tokens)
- Cohere - Fallback embeddings (free: 1K calls/month)
Total setup time: 5 minutes
Monthly cost: $0 (free tiers cover most users)
📚 Commands
universal-rag-mcp init # Setup wizard
universal-rag-mcp status # Check configuration
universal-rag-mcp config # Show config location
🤝 Contributing
Contributions welcome! Open an issue or PR.
📄 License
MIT License - See LICENSE
🔗 Links
- NPM Package: https://www.npmjs.com/package/@sid7vish/universal-rag-mcp
- GitHub Repo: https://github.com/Sid7on1/universal-memory-mcp
- Complete Guide: GUIDE.md
Made with ❤️ by Siddharth Vishwanath
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
Neon Database
MCP server for interacting with Neon Management API and databases
E2B
Using MCP to run code via e2b.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.