"Using a Cursor to Operate a Local Computer" matching MCP servers:

Enables local web crawling and scraping through MCP, providing tools to fetch pages as Markdown, extract structured data with CSS selectors, and capture full-page screenshots while managing a shared browser instance.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Enables web search, content extraction, question answering, and RAG context generation using Tavily API with Cursor-compatible underscore-named tools.

Provides accessibility testing capabilities through CLI, helping identify accessibility issues in web applications using axe-core and Puppeteer.

Pixel-level browser automation MCP server that drives a real Chrome browser using screenshots as vision input and OS-level mouse/keyboard as output, evading anti-bot detection.

Demonstrates using Playwright with the Model Context Protocol (MCP) to enable large language models to automate browser interactions, with an example of cursor-based pagination against the GitHub GraphQL API.

Fetches a URL and returns the main content as clean Markdown, using plain HTTP when possible and headless Chromium for JavaScript-rendered or bot-protected pages.

A lightweight MCP server for reading public YouTube data, offering tools to fetch video transcripts, playlist contents, and video metadata without requiring an API key.

Enables Claude to fetch web pages from the user's own local network connection instead of AI datacenter IPs, including optional authenticated sessions, with verdicts for bot challenges, login walls, and other failures.

A headless, agent-controllable real browser as an MCP server that enables AI agents to navigate, click, fill, eval JavaScript, and take screenshots on localhost and allowed hosts, with no GUI required.

Provides web scraping, crawling, and site mapping capabilities by connecting directly to a self-hosted Firecrawl instance. It enables users to extract website content in markdown format and manage crawling jobs without an external API key.

Local-first realtime web research MCP for LM Studio with keyless SearXNG, clickable citations, adaptive deep research, provider health, and one-click Windows startup.

MCP server that fetches remote or local HTML resources and converts them to Markdown, enabling AI clients to summarize or process web content.

An MCP server that automates converting diverse content sources like WeChat articles, YouTube videos, and various document formats into AI-generated outputs such as podcasts and slide decks via Google NotebookLM. It integrates specialized tools for web scraping, OCR, and file transformation to facilitate seamless content generation through natural language.

Lightweight MCP server for controlling a Windows Chrome instance from WSL, designed for AI coding agents with minimal token overhead and human-in-the-loop support.

Enables tool-calling LLMs to search the internet, capture website images, extract webpage text, and more via a local MCP server.

Enables converting webpages into structured JSON using CSS-selector schemas, with anti-bot handling and support for protected pages.

Enables converting any webpage to clean LLM-ready markdown, with extraction, article, and news modes, using a real browser with anti-bot handling.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Enables AI agents to fetch one or many web pages concurrently and receive clean, LLM-ready Markdown with navigation, ads and boilerplate stripped away, plus extracted metadata such as title, description, author, Open Graph tags and canonical URL. It runs locally over stdio with no API key or account, requiring only a single command.