"Information on RAG Documents or Processing" matching MCP servers:

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

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.

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

"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.

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.

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.

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

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

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.

AI-native web scraper: scrape, crawl and map any site to clean markdown over stdio. MIT-licensed.

MCP server for On-Call Health burnout analysis. Connects AI assistants to your on-call data for workload insights.

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.

Local-first RAG MCP server that indexes local documents and provides hybrid search (semantic + keyword) with file ingestion, URL fetching, and a CLI, keeping data on-device.

An MCP server that enables LLMs to convert HWP and HWPX documents into Markdown for analysis and processing. It supports document conversion via local file paths or Base64 content across various MCP-compatible clients.

MCP server that lets agents edit real Microsoft Word (.docx) documents - tracked changes, tables, styles, comments, content controls, and document properties - with every edit validated and previewed before saving. Built on the Open XML SDK (no Word automation); reads and writes documents in place through filesystem or SharePoint storage.

Enables generic CRUD operations on ERPNext/Frappe DocTypes via MCP tools, allowing users to interact with ERPNext data like documents, reports, and schema through natural language commands.

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.

Enables defect management on the SEPP platform, allowing users to query defects, retrieve user project information, and set up automated monitoring with alerts for new or unresolved defects via webhook or email.