"Search for information about 'rag'" matching MCP servers:

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.

A Model Context Protocol server that provides web search capabilities using Google Custom Search API and webpage content extraction functionality.

Enables broad web search for current, time-sensitive information, returning short title, URL, and snippet results rather than full pages. It supports region and result-count parameters through a keyless multi-engine backend.

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.

Provides AI-driven web search, page fetching, and site mapping with real xAI citations, enabling LLM clients to access up-to-date external information.

Gives Claude control of a real, headed Chromium browser via Playwright, enabling web navigation, clicking, typing, screenshots, and JavaScript evaluation.

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

Enables AI assistants to fetch, search, and organize menu information from For Five Coffee café. Provides access to complete menu data, category filtering, and item search capabilities through both MCP and REST API interfaces.

A Model Context Protocol server that enables web searching using the Serper API for Google search results, with optional web page content fetching.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

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.

Integrates the Brave Search API to provide web and local search capabilities, including news, articles, and business information. It features smart fallbacks from local to web search and supports pagination and freshness controls.

Enables AI agents to perform web search, extraction, and research across multiple provider backends with persistent multi-key rotation and auditable routing. Supports MCP, CLI, and Agent Skill entry points.

A Model Context Protocol (MCP) server for integrating Google Search capabilities into AI applications.

Enables one-call parallel querying across multiple search engines, aggregating and deduplicating results while automatically falling back to mainland engines when overseas sources are unreachable.

Provides keyless, privacy-focused web search through DuckDuckGo and SearxNG via MCP, with token-efficient tool discovery and caching.

Aggregates security research articles from WeChat, QAX Butian, and Xianzhi community, with optional KimiCode web search. Supports smart deduplication, article fetching, and anti-bot measures.

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.