"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.

Enables Codex to generate and edit images through an existing Responses API relay, saving PNG, JPEG, or WebP files to the current project or a specified directory.

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 local hybrid search over files by combining semantic vector and full-text BM25 retrieval, with MCP stdio/HTTP support, OAuth 2.1 authentication, and tools for reading and converting documents to Markdown.

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 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.

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

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.

Enables AI agents to access a local-first personal context and memory layer through MCP tools for bootstrapping user context, semantically searching Markdown vault knowledge, reading files, listing topics, and adding controlled memories. It provides deterministic context retrieval, provenance-cited vector search, and secure vault operations while keeping data local and model-independent.

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

Enables AI coding agents to audit and sweep away transient scratch directories, bloated test caches, and forgotten probe scripts in a workspace, with dry-run previews to guarantee nothing tracked or production-related is touched. It also detects zombie background dev servers still holding common ports like 3000, 5173, and 8000.

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.

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.

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 autonomous agents to securely access and manage virtual file systems, records, schemas, SQL and Mongo queries, and RAG search through scoped MCP tools, while supporting binary transfers via presigned S3 recipes.

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.

MCP server for reading and writing .xls (Excel 97-2003) files, enabling data manipulation, sheet listing, and metadata retrieval.

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

Enables LibreChat agents to manage per-user private files, persistent documentation, RAG indexing and semantic search, and publish files via secure opaque public links.

A local RAG server that enables document indexing and sentence window retrieval across multiple file formats like PDF, MD, and DOCX. It supports both local Hugging Face models and OpenAI embeddings for efficient context-aware querying through the Model Context Protocol.

Provides a production-ready Model Context Protocol server with dual STDIO and Streamable HTTP transports, enabling file operations, memory, database queries, RAG, web search, GitHub integration, background tasks, and prompt-based workflows.

MCP server for indexing, semantic search, and generation of multi-format documents. Exposes 13 tools over JSON-RPC 2.0 so an LLM can search your local PDF, Excel, and Word files, and create or edit Excel and Word documents.

Archive Agent is an open-source semantic file tracker with OCR + AI search (RAG) and MCP capability.