"Information about RAG (Retrieval-Augmented Generation) or rag-related topics" matching MCP servers:

A multi-agent Retrieval-Augmented Generation system exposed as an MCP server. Ask a question and a LangGraph pipeline plans the retrieval, pulls evidence from a pgvector knowledge base, optionally augments it with live web research, drafts a cited answer, and then self-critiques it for grounding — revising until the answer is supported by the sources.

Enables ingestion and semantic search over text documents using PostgreSQL + pgvector and OpenAI-compatible embeddings, allowing any LLM agent to retrieve relevant chunks for grounded answers.

"primitive" RAG-like web search model context protocol server that runs locally. ✨ no APIs ✨

Provides RAG tools with local vector retrieval and web fallback using Firecrawl, enabling document ingestion and querying through MCP stdio transport.

Enables RAG over messy PDFs — extract, chunk, embed, and search scanned, multi-column, and table-heavy documents.

Searches local markdown files using TF-IDF retrieval and serves full documents as resources.

A local MCP server that enables LLMs to securely search and read files within designated Google Drive folders. Supports Google Docs, Google Sheets, PDFs, and plain text with strict folder-scoping via service account authentication.

An MCP server providing web search, image search, and page scraping tools to LLMs without requiring API keys.

Enables asking natural language questions about local videos, using Whisper transcription, ChromaDB vector storage, and Groq for timestamped answers via MCP.

Serves UltraRAG memory to agents over stdio MCP, providing project-local and per-user global memory. It lets agents read and append standing memory and daily dialogue rounds in UltraRAG's format, with an optional browser view.

Enables natural-language and keyword search across Obsidian notes, returning reranked passages with provenance, and supports reading notes and incremental indexing.

Multi-provider image generation MCP server that enables image generation from Claude Desktop, Claude Code, or any MCP client using OpenAI, Google Gemini, Stable Diffusion, or a placeholder provider.

A hosted multimodal RAG MCP server that enables natural language queries over text and visual content (PDFs, images, etc.) with verifiable citations, easily run via npx with a Calypso API key.

RAG-powered MCP server that indexes and searches Tezos protocol specs, TZIPs, and Octez source code, enabling semantic search and expert guidance on Tezos topics.

Rust-powered PDF toolkit over MCP: create, read, and analyze PDFs; extract text and entities for RAG; convert to Markdown; split/merge/rotate/reorder pages; manage form fields and annotations; encrypt documents. Runs locally via uvx oxidize-mcp.

An MCP server that protects AI agents and RAG systems from adversarial poisoning attacks like prompt injection, steganography, and data anomalies through multi-layer sanitization, entropy-based detection, and consensus verification.

Ask about the Saudi economy in plain English or Arabic. No API key or database required.

This MCP server provides comprehensive Google Workspace integration (Gmail, Drive, etc.) with multi-user OAuth. Unique features include RAG-powered natural language to Chat card rendering, runtime Jinja2 macro creation, and dynamic tool management.

A Model Context Protocol server that retrieves detailed geographic information about IP addresses using the ipinfo.io API, helping determine user location and network details.

Enables natural language queries to Yandex Metrika analytics, allowing users to ask questions about traffic, sources, and user behavior without dashboards or SQL.