PDF RAG server for cursor.

Local-first RAG desktop app & official MCP Server. Let any AI instantly search your private Markdown, PDF, and 1290+ document formats. (本地优先的 RAG 桌面端与官方 MCP 服务器。让任意 AI 瞬间检索你的私有 Markdown、PDF 及 1290+ 种文档格式。)

🦀 High-performance local RAG server in Rust that integrates with Claude Desktop via MCP. Search PDF documents privately using Ollama embeddings - no external API calls.

CLI tool for building production RAG systems from Markdown, CSV, and PDF documents using hybrid search (BM25 + vector) with OpenSearch. Features MCP server, Slack bot, Web UI, multi-source ingestion (local/S3/GitHub), and multi-provider embeddings (Bedrock/Gemini).

MCP server for intelligent paper/PDF management with RAG capabilities

MCP server for intelligent document ingestion using Docling. Convert PDFs, DOCX, images, audio & more to clean Markdown for AI/RAG pipelines. Mac M2 optimized with MLX acceleration, VLM processing & queue management.

Mcp server with local RAG on pdf and word documents and web search

RAG pipeline for documents (Markdown, PDF, images). 10-step hybrid search, LLM enrichment, taxonomy, MCP server. Cloud or local.

An MCP server that provides a RAG database for PDF documents.

Local MCP server for RAG over PDFs, DOCX, and plaintext files.

RAG server for quantitative finance research — layout-aware PDF/LaTeX/notebook ingestion, hybrid BM25 + BGE-M3 retrieval with reranking, local LLM synthesis, REST API and MCP server.

Self-hosted PageIndex MCP server for Claude Code — vectorless RAG for PDFs

Athena MCP RAG Server: Production-ready Pinecone-powered Retrieval-Augmented Generation server for Claude Desktop, with PDF ingestion, teacher tools (explain, study plans, quizzes)

MCP server for Microsoft Markitdown - Convert documents (PDF, DOCX, PPTX, images) to clean Markdown for RAG/LLM workflows on Apify platform

High-performance local MCP server for Scientific RAG. Optimized for extracting tables, formulas, and references from technical PDFs using PyMuPDF4LLM and Ollama.

A local-first AI stack for LM Studio. Docker-powered RAG pipeline with pgvector, SearXNG, and TEI embeddings, plus 8 pre-wired MCP tool servers for web search, PDF reading, file access, persistent memory, screenshots, and more. No API keys, no cloud AI — everything runs on your hardware.

ArXiv Intelligence MCP is a research assistant server that lets AI clients (Claude Desktop, Cursor) search ArXiv, download and parse PDFs via IBM DocLing, and store paper embeddings in a local ChromaDB vector store. It exposes RAG-powered Q&A tools over your personal paper library through the Model Context Protocol.

Chatbot RAG PoC with an Indexer for Pdfs etc., MCP Server, Agentic AI,

RAG MCP Server for Claude Code — Semantic search over PDFs, code, and documents

Multi-source MCP RAG server for files (Markdown, PDF) from local folders and GitHub repositories

Config-driven RAG pipeline: PDF parser, semantic search, and MCP server for any document corpus

MCP server for RAG over messy PDFs — semantic search, OCR, table extraction. Works with Claude Desktop, Claude Code, Cursor, and any MCP client.

An MCP server that wraps RAG-Anything to provide multimodal RAG over local documents (PDFs, Office, images, tables, equations) and expose it as tools to MCP-aware clients like Claude Desktop.

An MCP (Model Context Protocol) server that ingests PDF files, creates embeddings, and provides RAG (Retrieval Augmented Generation) search capabilities with API key authentication.

RAG MCP server for Claude Code — hybrid search (vector + BM25), code-aware chunking, PDF support. Uses Ollama nomic-embed-text + LanceDB. Fully local, zero API costs.

A multimodal RAG - MCP server for research paper reading assistance. Ingest PDFs from local files or arXiv, then semantically search or ask queries on the papers.

Shared core library for Microchip MCP servers and RAG systems. Provides production-ready components for document extraction (PDF/PPTX), vector storage (Qdrant), embeddings (sentence-transformers), LLM integration, and security utilities. Enables thin MCP server wrappers around reusable business logic.

Multi-provider LLM travel recommendation agent with RAG-enhanced suggestions, Qdrant vector search, MCP server, and Claude Code integration. Generates comparative PDF reports with real flight data.

This project implements a Retrieval-Augmented Generation (RAG) chatbot using Streamlit and the MCP server. Users can upload PDF files, and the chatbot retrieves relevant information from the PDFs to answer natural language questions.

A Model Context Protocol (MCP) server that provides powerful RAG (Retrieval-Augmented Generation) capabilities for PDF documents. This server uses ChromaDB for vector storage, sentence-transformers for embeddings, and semantic chunking for intelligent text segmentation.