"Web scraping and content extraction" matching MCP servers:

An MCP server that provides a tool to extract text content from local PDF files, supporting both standard PDF reading and OCR capabilities with optional page selection.

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.

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.

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.

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

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.

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

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

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

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.

Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.

Enables MCP-compatible clients to access reusable AI content-generation tools for creating blogs, social posts, SEO content, research summaries, and more through the FastAPI backend.

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

A hosted MCP server providing 15 media and data tools for AI agents, including web search, news, content extraction, summarization, translation, moderation, script writing, text-to-voiceover, transcription, subtitles, viral-clip discovery, and short-form video editing.

Provides web search, content extraction, and AI summarization capabilities using the GLM-4.7-Flash model. It enables users to perform web searches, fetch website data, and generate concise content summaries through integrated tools.

Exposes TaskFleet's pay-per-call AI task APIs as MCP tools, including web search, scraping, extraction, translation, code review, summarization, and wallet intelligence. Payments are handled via x402 (USDC on Base) with no accounts or API keys.

Enables AI assistants to fetch and analyze web content from URLs through MCP protocol. Supports batch processing, content extraction, summarization, and metadata extraction with intelligent filtering of ads and navigation elements.

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

Lets coding agents such as Claude Code and Codex hand summarising, field extraction, classification and OCR to the free, offline on-device model for Apple Foundation Models on macOS 27. One Rust binary, installed with Homebrew.

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.

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

Lets any AI agent score and simplify its own text before it reaches a human, using Flesch readability metrics and plain-language rewrites entirely on the local machine.

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.

Provides MCP-compatible AI clients with offline text analysis and rewriting tools, including statistics, extractive summaries, keywords, readability scores, case conversion, entity extraction, and diffing, all running locally without API keys or network calls.

Enables analysis of clinical trial protocols using MCP tools for document listing, entity extraction, adverse event clustering, and summarization.

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.

Enables context compression for Claude Code with Thai language support, reducing token usage by 50-88% while preserving full recoverability of original content.

Turns plain text or Markdown, web pages, and local PDFs into editable Markdown outlines that can be rendered as standalone, offline-capable interactive HTML mind maps. Works with any MCP client with no API key required, since the connected model writes the final outline from a draft and cleaned source text.