"Information about RAG" matching MCP servers:

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 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.

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.

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.

Enables Claude to read and analyze project schedule files in OmniPlan (.oplx) and Microsoft Project (.mpp) formats, answering questions about tasks, milestones, resources, and progress.

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.

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.

MCP server that allows AI agents to read, search, summarize, and answer questions about local PDF, DOCX, XLSX, and TXT files through five tools.

Enables natural-language queries about disk usage by driving WizTree scans and analyzing cached CSV snapshots. Users can find large files, duplicate data, folder breakdowns, and more without repeatedly rescanning the disk.

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

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.

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

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.

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

A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.

Converts CAD drawings (DXF/DWG) into structured data, enabling Claude to read drawings and answer questions about their content.

Local RAG over a directory, served as an MCP tool plus CLI, with incremental indexing, zero-config defaults, and offline CPU-only operation.

A modular MCP server suite that provides core tools, long-term memory, knowledge RAG, skills registry, and external integrations for AI agents.