"Chat with RAG (Retrieval-Augmented Generation)" matching MCP servers:

An MCP server providing web search, image search, and page scraping tools to LLMs without requiring API keys.

Enables AI agents to fetch, crawl, extract, and search web content through a unified set of tools, with automatic routing to specialized backends.

A Model Context Protocol server that analyzes webpage design structures, providing detailed layout, navigation, content, form, image, and link information from a given URL.

An open-source MCP server providing AI agents with neural web search via Exa and tiered web fetch (Exa, local browser, Firecrawl) as a drop-in replacement for built-in web tools, preserving provenance and guarding against SSRF.

Enables MCP-capable agents to perform reliable web search and content fetching through a single server that automatically fails over across multiple providers. It handles keyed or keyless authentication automatically and returns clean Markdown or text results.

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 LLMs to fetch Israeli weather forecasts by controlling a real browser via Playwright, simulating human interactions like typing and clicking on a weather website.

An MCP server that enables LLMs to automate browser interactions using Playwright to fetch real-time Israeli weather data.

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 ✨

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.

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.

An MCP server that uses Google Gemini and Playwright to fetch current weather for Israeli cities, extracting data from live websites to answer queries in Hebrew or English.

Enables retrieval and cleaning of official documentation content for popular AI/Python libraries (uv, langchain, openai, llama-index) through web scraping and LLM-powered content extraction. Uses Serper API for search and Groq API to clean HTML into readable text with source attribution.

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.

Enables collection and scoring of sales chat conversations via CDP, computing response times and generating evidence-linked LLM quality reviews.

An MCP server for integrating with the Brave Search API, and it supports HTTP proxying.

mcp-fetch