"Scroll modules for reading web page content" matching MCP servers:

Enables AI agents to extract clean, structured web content (articles, tables, links, visual layouts) optimized for LLM token efficiency, with fast response times and optional JavaScript support.

Analyzes scroll-triggered animations on any webpage using Playwright, extracting GSAP, ScrollTrigger, Lenis, and CSS code via AST and runtime detection.

Enables Claude Code or Codex CLI to see the exact sentence and section you are viewing in Chrome, so you can discuss books with context, take notes, and track reading progress.

Enables local Chrome DOM access through MCP for reading visible page text, operating DOM controls, and managing tabs without screenshots or screen sharing.

Drop a single script into a web UI and the page itself exposes DOM inspection, interaction, and diagnostic devtools to coding agents through document.modelContext, with no server, LLM, or chat UI involved. It also lets an app register its own domain-state tools, so agents can reach state that the DOM cannot reveal.

Enables AI assistants to monitor web pages for content changes and receive alerts when changes occur.

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 server that uses headless Chromium (Puppeteer) to capture pixel-perfect screenshots and extract DOM from URLs, with LLM-friendly step-based workflows.

Enables monitoring web pages for changes using Playwright, storing snapshots in SQLite, and optionally analyzing changes with an LLM for business impact assessment.

Enables browser-based web page fetching with automatic cookie management and CSS selector extraction, supporting JavaScript rendering and authenticated sessions through a Chrome extension.

Enables exporting Apple Safari Reading List entries to JSON and adding new items via MCP on macOS.

Enables an AI agent to read and operate the Chrome or Edge tabs you are already using — titles, URLs, text, HTML, screenshots, clicks, typing, scrolling, and tab management — via a browser extension and native messaging, without restarting the browser, switching profiles, or opening a debug port. It exposes these capabilities as 19 MCP tools, with access limited to explicitly shared tabs and hardened by per-tab, origin-bound grants plus domain allow/deny lists.

Enables AI assistants to list, search, add, update, remove, restore, and export the user's Chrome reading-list items through local extension-backed tools, with backups for deletions.

MCP server that fetches raw HTML content from a given URL to provide web context to LLMs.

Fetches any public web page and provides SEO foundation snapshots and prose readability analysis.

Enables agents to search the live web and fetch URLs as clean Markdown, returning ranked search results and paginated page content through two lightweight tools.

Enables reading web pages and PDFs as clean Markdown, extracting main content and letting agents query for relevant passages, outline sections, search in-page, and list links while respecting robots.txt and blocking private addresses.

Given a company domain, finds specified page types (like pricing or careers) on the company's own website and returns the URL, discovery method, and confidence score, optionally extracting structured data from the page.

Enables live-web research by providing stateless browsing, link extraction, and page search capabilities via Playwright, allowing agents to fetch and analyze web content without session management.

Gives AI agents local web search and page reading with no API keys, layering a SearXNG-backed search cache with browser-based fallbacks and returning clean page text from HTML, PDF, JSON, and archived snapshots. Fetches run in Docker alongside the search engine with SSRF protection, egress filtering, and untrusted-content marking so agents can safely retrieve live web data.