"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 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.

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 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.

A local MCP server for low-token co-reading: import a book, split it into chapter-sized chunks, read it chunk by chunk, and keep notes so a session can resume without re-reading the whole book.

Extract content from URLs, documents, videos, and audio files using intelligent auto-engine selection. Supports web pages, PDFs, Word docs, YouTube transcripts, and more with structured JSON responses.

A local MCP server that gives Claude a durable reading room for EPUB and plain text books, enabling chunk-by-chunk navigation, annotations, progress tracking, and shared margin cards.

Enables a shared reading room where users and Claude can import EPUB or text books, read chunk-by-chunk, annotate passages, search, track progress, and resume from unread sections.

An MCP server for fetching and scraping web pages, providing fetch_url and scrape_url tools.

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.

Provides AI agents with structured short-form content mechanics including hooks, script structures, retention strategies, and CTAs, along with auditing tools to avoid common posting failures.

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 reading and verifying C2PA Content Credentials from images and videos through both embedded manifests and invisible watermarks. Supports direct filesystem access, URL checking, and provides structured provenance data including creator identity, AI generation info, and content authenticity.

SERP-based content scoring and optimization with 7 SEO categories.

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.