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

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

Enables local EPUB reading with AI agents, supporting annotations, parallel editions, and MCP tools.

A 4-stage reading companion that helps users set reading goals, discover books, track progress, and deepen learning through reflection, integrated with Claude Desktop.

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.

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.

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

A low-token human-AI co-reading MCP tool that imports local EPUB/TXT/Markdown books into chunks, enabling AI to read only relevant fragments and write co-reading results to long-term reading notes and progress files.

Enables AI clients to manage a self-hosted content hub: create, edit, publish, and update articles across multiple platforms, plus AI writing and account management.

AutomateLab Content Distribution publishes content across DEV.to, Hashnode, GitHub Discussions, Reddit and Bluesky, with browser workflows for LinkedIn, Medium and X. Tracks publishing state and adapts content per platform. Product and documentation: https://automatelab.tech/products/mcp/content-distribution-mcp/

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 document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.

Enables editorial content QA over the Model Context Protocol with four local tools that analyze readability, AI-sounding language, SEO on-page factors, and produce full reports where every finding includes an actionable fix.

Provides content agents with structured search over editorial guidelines, visual templates, and past post outcomes, enabling auditable proposals that cite rule IDs.

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.

An MCP server that deterministically scores landing pages on conversion-critical signals and blocks ad spend on low-quality pages to prevent wasted budget.

Enables MCP-capable agents to perform local web research under a declared plan with session budgets, user-approved limit extensions, and guardrails for safe searching, page fetching, content extraction, and audit logging.

Maps any source asset (e.g., long video, podcast, blog) to all platform formats (TikTok, Reels, Shorts, etc.) with per-platform adaptation rules, enabling a 'film-once-cut-many' content workflow.