"How to scrape web content" matching MCP servers:

A Python MCP server for web research that enables fetching web pages, searching, batch-fetching, extracting links, and summarizing content via client-side sampling, with optional local file access.

An MCP server that enables web searching, URL content extraction, and summarization without requiring API keys. It also provides advanced mathematical evaluation and multi-language Wikipedia summary retrieval tools.

MCP server that provides web content fetching, summarization, comparison, and extraction capabilities, handling up to 20 URLs per request.

Allows you to search the web using DuckDuckGo and optionally fetch and summarize content from search results.

Enables intelligent web searching using SearXNG with content crawling via Creeper, then summarizes webpage content using LLM to avoid token limit issues. Supports smart filtering with domain blacklist/whitelist and optional LLM-based relevance filtering.

Provides content intelligence tools for AI agents, including extraction, analysis, research, comparison, monitoring, and briefing, powered by free LLMs with pay-per-call or subscription pricing.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

MCP server for summarizing content from Baidu Netdisk, local files, Bilibili, X, and web articles, producing Obsidian notes with bidirectional links and Feishu digests.

Provides web search, URL fetching, summarization, math evaluation, and Wikipedia tools for LM Studio without needing an API key.

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

Enables AI-powered web searches using DuckDuckGo with automatic summarization via Google's Gemini AI. Supports both summary and detailed analysis modes for search results.

Provides clean, bounded web content to AI by filtering HTML noise and optionally summarizing, preventing context window overflow.

A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.

tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.

MCP server that searches the web, reads pages, and returns concise summaries with cited sources via the research_web and read_url tools.

A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.

Enables LLMs to interact with Fathom.video API for managing meeting recordings, retrieving transcripts and AI-generated summaries, searching meeting content, and accessing analytics and team data.

Enables AI agents and MCP clients to browse Roomtone meeting notes, add YouTube or pasted-text sources, generate summaries, ask questions answered from transcripts, and retrieve raw transcript text. Recording itself stays in the Roomtone app, so the server only reads and adds to existing meetings.

23 developer & data API tools for AI agents - IP/DNS/WHOIS/SSL lookups, web scraping & screenshots, text AI (summarize, translate, sentiment, grammar, redact), and dev utilities (hash, UUID, QR, JWT, cron, IBAN/VAT/email validation, breach check).

Enables production-grade web research through MCP, combining local SearXNG search with hosted fallback providers, fetch and crawl tools, summarization, and budget guardrails.