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

An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.

A TypeScript MCP server that allows querying documents using LLMs with context from locally stored repositories and text files through a RAG (Retrieval-Augmented Generation) system.

A local hybrid-search MCP server that enables coding agents to query files and folders using natural language, returning relevant code chunks with exact source paths. Everything runs on-device with no API keys or network calls.

Enables sandboxed file operations via MCP tools, resources, and prompts, with a Claude CLI client and Groq-powered web UI for file CRUD, search, code review, and documentation generation.

MCP server that enables local hybrid semantic and keyword search over private PDF, DOCX, Markdown, and text documents without sending data to embedding APIs.

Provides intelligent retrieval capabilities for local files by scanning directories, generating vector indexes, and enabling semantic search through RAG (Retrieval Augmented Generation) with incremental indexing support.

A local-first Graph-RAG system that combines ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q\&A over your Obsidian vault.

Enables RAG (Retrieval-Augmented Generation) with tools for vector search, document access, and OpenAI integration, plus MySQL storage and file system operations via MCP.

Enables advanced semantic search and document management by integrating the GroundX API with Claude Desktop and GitHub Copilot. It supports local file uploads, website crawling, and Google Drive synchronization for RAG workflows.

A focused local-paper RAG MCP server that imports PDFs, indexes them into SQLite and ChromaDB, and retrieves section-aware paper chunks for use with Claude Code, Codex, or any MCP client.

Provides AI agents with local file-processing capabilities for token counting, RAG chunking, CSV/JSON conversion, QR generation, and more, while keeping documents private on the user's machine.

MCP server that enables semantic search over local PDF collections using local RAG, with automatic indexing of new documents.

Enables PDF generation from HTML, text, and Markdown content with customizable formatting options. Provides secure cross-platform PDF creation tools that automatically save to user directories like Downloads, Documents, or Desktop.

mcp using PyPDF2 to: • merge-pdfs • extract-pages • search-pdfs • merge-pdfs-ordered (merge in user spec. order) • find-related-pdfs (regex extracted text for related PDF files)

Enables triage, installation validation, and controlled automation of X-Ways Forensics and related tools through structured MCP tools for agents.

Enables vectorless RAG by letting LLM clients like Claude and Cursor parse documents, inspect outlines, and retrieve specific sections with heading breadcrumbs. Supports PDF, Word, HTML, and PowerPoint without LLM calls or heavy ML models.

Provides tools for AI clients to scan, match, and scrape TMDB metadata for local media files, with safe sidecar writing or full Jellyfin-style reorganization including file renaming and NFO generation.

Enables read-only search and retrieval of your email across multiple IMAP accounts through a local notmuch index, served over authenticated HTTP for MCP clients like Claude or Codex.

A sophisticated MCP server providing powerful file search capabilities including single file search, recursive directory search, and file information retrieval.

A simple MCP server for local documentation with RAG capabilities, enabling AI assistants to access and search local documents.