"Web Scraping" matching MCP servers:

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.

A Model Context Protocol server that allows LLMs to interact with web content through standardized tools, currently supporting web scraping functionality.

Provides MCP tools for web scraping, including smart fetching, proxy rotation, and browser rendering to bypass anti-bot challenges and render JavaScript-heavy sites.

A fast, dependency-light MCP server that converts web pages into clean Markdown, structured metadata, and classified links for language models.

Enables agents to perform full-text search and read Hermes Agent documentation offline from a local cache, without scraping the site.

A production-ready Model Context Protocol server that enables language models to leverage AI-powered web scraping capabilities, offering tools for transforming webpages to markdown, extracting structured data, and executing AI-powered web searches.

An MCP server that runs Apify scraping actors with quality-gated validation, scoring, and retries, returning embedding-ready chunks for AI agents.

Enables AI assistants to perform comprehensive research by searching Google, mining Reddit discussions, scraping web content with JS rendering, and synthesizing findings with citations into structured context.

A basic MCP server setup guide demonstrating how to configure and run Python-based MCP servers with integration examples for Bright Data web scraping and Apify Actors for product data collection.

Enables AI agents to fetch any web page and receive clean, token-efficient Markdown, escalating only as needed from direct HTTP with browser TLS fingerprints to headless-browser rendering and residential proxies when a site blocks access. Supports question-focused passage retrieval with BM25 ranking, pagination, caching, JS rendering control, and safe-by-default restrictions on local and private-network URLs.

An enterprise-grade Model Context Protocol server for high-performance web analysis that discovers subpages, provides AI-based page summaries, and extracts structured content for RAG using FastMCP and FastAPI.

A focused MCP server that provides a single web_search tool for web searches, integrating Tavily and Brave with automatic fallback and key rotation.

MCP server that fetches web pages and uses local Qwen models to answer questions about their content, with site-scoped search and map-reduce chunking for long pages.

Provides web search capabilities to Claude AI using the Anthropic API, allowing LLMs to access up-to-date information from the web with customizable domain filtering.

A fast web reader for AI assistants, served over MCP. It reads web pages and PDFs and returns only the passages that answer the question, not whole pages. It runs locally and keeps nothing.

Interact with WebScraping.AI API for web data extraction and scraping

MCP server providing tools for web scraping, browser automation, computer vision, audio transcription, and RAG via API.

Web scraping, crawling, and structured data extraction for AI agents. 5 tools: scrape (clean markdown from any URL), crawl (entire sites), map (discover URLs), extract (structured JSON), and search. 833ms avg latency, single binary, self-hostable.

A Model Context Protocol server that gives AI assistants access to 7 search providers with intelligent auto-routing. Analyzes query intent and picks the best provider automatically — no manual switching needed. Install, configure your keys, and go.

Web scraping for AI agents: scrape, map, crawl and batch public pages into Markdown, tables and JSON, with an Evidence Record on every page. Blocked, empty and wrong pages come back as such, with the reason.

A Model Context Protocol server that enables AI assistants to perform advanced web scraping, crawling, searching, and data extraction through the Firecrawl API.

Enables MCP-compatible AI clients to extract live web content and convert it into structured Markdown for LLM ingestion, RAG pipelines, and agentic workflows.

Enables AI assistants to query and search library documentation from GitHub repositories or web pages using RAG and web scraping.

Enables LLMs and AI agents to access real-time web data, search websites, and navigate the web without getting blocked. Includes 5,000 free monthly requests and supports web scraping, browser automation, and bypassing geo-restrictions.

A local web scraping MCP server with RAG capabilities that provides intelligent web search, content extraction, and screenshot tools without requiring API keys.

A Model Context Protocol server enabling AI assistants to scrape web content with high accuracy and flexibility, supporting multiple scraping modes and content formatting options.

Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.

An MCP server that enables AI models to perform Google Web searches using the Gemini API, complete with citations and grounding metadata for accurate information retrieval. It is compatible with Claude Desktop and other MCP clients for real-time web access.

A comprehensive Model Context Protocol server for content summarization that supports web scraping, file reading, content summarization, and topic-based summarization features.

Enables web search capabilities through the Tavily API. Allows users to search the web for information using natural language queries via the MCP protocol.