rag_mcp_server
by aksaini2003
Overview
Provides a RAG (Retrieval Augmented Generation) tool as an MCP server endpoint, leveraging Google Generative AI embeddings and FAISS for document retrieval.
Installation
python server.pyEnvironment Variables
- GOOGLE_API_KEY
Security Notes
The server uses `FAISS.load_local` with `allow_dangerous_deserialization=True`. This is a critical security vulnerability as it allows arbitrary code execution if a malicious `vector-db` file is loaded. The server also exposes itself on `0.0.0.0:8000`, which requires proper network security.
Similar Servers
pageindex-mcp
Provides vectorless, reasoning-based RAG capabilities for LLMs to navigate and retrieve information from hierarchical document structures, primarily for long PDFs.
Archive-Agent
An intelligent file indexer with powerful AI search (RAG engine), automatic OCR, and a seamless MCP interface for document retrieval and question answering.
qdrant-loader
The QDrant Loader MCP Server provides advanced Retrieval-Augmented Generation (RAG) capabilities to AI development tools by bridging a QDrant knowledge base. It offers intelligent search through semantic, hierarchy-aware, and attachment-focused tools, integrating seamlessly with MCP-compatible AI tools to provide context-aware code assistance, documentation lookup, and intelligent suggestions.
local_faiss_mcp
Provides local vector database functionality using FAISS for Retrieval-Augmented Generation (RAG) applications, enabling semantic search and document ingestion for AI agents.