MCP Server with FAISS for RAG
Description
# MCP Server with FAISS for RAG This project provides a proof-of-concept implementation of a Machine Conversation Protocol (MCP) server that allows an AI agent to query a vector database and retrieve relevant documents for Retrieval-Augmented Generation (RAG). ## Features -…
About
# MCP Server with FAISS for RAG This project provides a proof-of-concept implementation of a Machine Conversation Protocol (MCP) server that allows an AI agent to query a vector database and retrieve relevant documents for Retrieval-Augmented Generation (RAG). ## Features - FastAPI server with MCP endpoints - FAISS…
Details
- Author
- ProbonoBonobo
- GitHub stars
- 7
- Downloads
- 335
- Categories
- Knowledge Base
Jump to
- FastAPI server with MCP endpoints
- FAISS vector database integration
- Document chunking and embedding
- GitHub Move file extraction and processing
- LLM integration for complete RAG workflow
- Simple client example and sample documents
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
MCP Server with FAISS for RAGCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install with pipx (pipx install -e .) or manually (pip install -r requirements.txt). Then use CLI commands like mcp-download, mcp-search-index, mcp-index, mcp-query, mcp-rag, and mcp-server. Optionally set GITHUB_TOKEN and OPENAI_API_KEY in .env. Start the server with mcp-server or python main.py, then query via MCP API at /mcp/action.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp server with faiss for rag": {
"sui-mcp-server": {
"command": "pipx",
"args": [
"ensurepath"
]
}
}
}
}McpServers
{
"sui-mcp-server": {
"command": "pipx",
"args": [
"ensurepath"
]
}
}MCP Server with FAISS for RAG
This project provides a proof-of-concept implementation of a Machine Conversation Protocol (MCP) server that allows an AI agent to query a vector database and retrieve relevant documents for Retrieval-Augmented Generation (RAG).
Features
- FastAPI server with MCP endpoints
- FAISS vector database integration
- Document chunking and embedding
- GitHub Move file extraction and processing
- LLM integration for complete RAG workflow
- Simple client example
- Sample documents
Installation
Using pipx (Recommended)
pipx is a tool to help you install and run Python applications in isolated environments.
1. First, install pipx if you don't have it:
```bash
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