"Information or uses related to a rag" matching MCP servers:

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Enables AI agents to search the web with clean page text, crawl websites into Markdown, extract articles and structured data, and monitor Google News and press releases for LLM context and RAG pipelines. It works with MCP clients and uses the user's own Apify API token for pay-per-result data retrieval.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.

Fetches web content and returns relevant chunks using RAG with semantic chunking, query-based scoring, and LexRank, supporting PDFs and 50+ languages.

"primitive" RAG-like web search model context protocol server that runs locally. ✨ no APIs ✨

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

Provides web crawling and RAG capabilities for AI agents, enabling scraping of websites, storing content in a vector database (Supabase), and performing semantic search over crawled data.

Crawls and indexes documentation websites to Supabase with vector embeddings for RAG, using smart sitemap discovery and Jina AI for fast content extraction with multi-project support.

An MCP server that automates converting diverse content sources like WeChat articles, YouTube videos, and various document formats into AI-generated outputs such as podcasts and slide decks via Google NotebookLM. It integrates specialized tools for web scraping, OCR, and file transformation to facilitate seamless content generation through natural language.

Web crawling and RAG implementation that enables AI agents to scrape websites and perform semantic search over the crawled content, storing everything in Supabase for persistent knowledge retrieval.

A database-agnostic MCP server that integrates web crawling with Retrieval Augmented Generation, supporting multiple AI providers and vector database backends for flexible and intelligent content retrieval.

Enables semantic search and retrieval-augmented generation (RAG) using Qdrant vector database. Supports indexing documents from URLs and local directories, with flexible embedding options using Ollama or OpenAI.

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Enables converting any webpage to clean LLM-ready markdown, with extraction, article, and news modes, using a real browser with anti-bot handling.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Converts X (Twitter) posts into JSON, PDF, PNG, Markdown, or Slack/Discord messages using public endpoints, no API key or login required.

Self-hosted MCP toolkit providing web search, Wikipedia, and arXiv access without mandatory API keys, delivered as a Docker Compose bundle.