"Understanding RAG (Retrieval-Augmented Generation or related topics)" matching MCP servers:

Enables AI agents to search private GitHub Pages by authenticating in a dedicated browser and retrieving indexed sections from a local SQLite database, with support for multiple sites and languages.

A BM25-based MCP server that enables document search and retrieval across structured domains of knowledge content, allowing Claude to search and reference documentation when answering questions.

Enables hybrid retrieval-augmented generation with semantic and keyword search over documents, supporting multiple formats and providing MCP integration for Claude Desktop.

A Model Context Protocol (MCP) server with Retrieval-Augmented Generation (RAG) for answering questions about imaginary SuperNova documentation. Enables semantic search over documentation using HuggingFace embeddings.

Enables cited, revision-aware retrieval over real IETF RFC chunks with zero LLM in the answer path, including graph-based supersession resolution and relationship queries via MCP tools.

Provides read-only MCP tools for hybrid semantic and keyword search over locally indexed PDF documentation, with citations and context retrieval for LLM agents.

An MCP server that enables users to query Kedro framework documentation using retrieval-augmented generation. It builds a local knowledge base from documentation files to help users navigate and apply Kedro's data science pipeline framework.

Retrieval-Augmented Generation system serving LangGraph documentation through the Model Context Protocol, enabling semantic search and context-aware responses.

A RAG MCP server that enables retrieval-augmented question answering over PyTorch documentation, with hybrid search (FAISS+Chroma, BM25) and source-cited responses from DeepSeek.

Provides coding agents with hybrid semantic and exact-identifier search across VHDL source, documentation, and general code, with cross-referencing and exact source attribution.

Enables hybrid search and agentic retrieval over Confluence pages via MCP tools, allowing Claude Desktop, Cursor, or Claude Code to search and retrieve Confluence content.

Transforms static gemini-cli documentation into a queryable RAG service, enabling developers to ask questions about Gemini CLI in natural language and receive instant, accurate answers based on the official documentation directly within their workflow.

MCP server for RAG-based search over 1C Enterprise configuration documentation, enabling natural language queries to find objects like справочники, документы, and отчеты.

Enables MCP clients to semantically search a local folder of markdown documents via a single search_notes tool, with embeddings generated locally by Ollama and support for excluding superseded or archived material.

Provides read-only retrieval of STM32 datasheet and reference manual content with exact citations, page numbers, register details, and source hashes so Claude can answer questions or generate code from verified evidence.

MCP server exposing a RAG knowledge base as read-only tools (search_knowledge_base, ask_knowledge_base, kb_stats, kb_diagnostic) for AI clients like Claude Desktop and Cursor, enabling token-efficient document retrieval and Q&A.

Standalone MCP server exposing agentic-RAG tools (hybrid search, article retrieval, category listing) over a pgvector-backed knowledge base with bearer-token auth, designed for deployment on Render.

Enables users to ask natural-language questions over FAQ markdown files and receive grounded, source-cited answers through the ask_faq tool over stdio.

Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.

Provides access to Godot engine documentation through a Retrieval-Augmented Generation (RAG) system using ChromaDB. It enables users to query processed Godot documentation and technical chunks for development assistance within MCP-compatible environments.