A fault-tolerant, stealth-enabled Model Context Protocol (MCP) server for web searching and content fetching. Built for AI Agents (Cursor, Claude Code, OpenCode), it uses a stealth browser engine to fetch pages, dynamically handles SPAs/React, and converts bloat into token-optimized Markdown.
Enables web search via Serper API with advanced search operators and webpage scraping capabilities to extract content in plain text or markdown format.
An MCP-native pipeline for collecting structured intelligence on higher education institutions using the WHED schema, enabling scraping, extraction, validation, and saving of profiles.
Exposes Amazon Nova Act web automation capabilities through the Model Context Protocol, enabling AI agents to perform browser tasks like navigation, data extraction, and form interaction.
An authless Cloudflare Workers server that provides tools to scrape, analyze, and answer questions about websites using Cloudflare's Browser Rendering and AI capabilities.
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.
Extracts people (names and titles) from a company's team, leadership, or about page given a domain. Uses Apify to crawl and return structured data, with optional filters for seniority and email inclusion.
An MCP server that uses Playwright to scrape Israeli weather forecasts from weather2day.co.il by automating a real browser, enabling an LLM to answer questions about current conditions and hourly forecasts for Israeli cities.
An MCP server that uses headless Chromium (Puppeteer) to capture pixel-perfect screenshots and extract DOM from URLs, with LLM-friendly step-based workflows.
An MCP server that uses Playwright to browse Israeli weather forecasts from weather2day.co.il, allowing LLMs to control a browser to fetch real-time weather data.
Automates Grammarly's web interface to check AI detection and plagiarism scores, then uses Claude to iteratively rewrite text until it meets target thresholds for humanized content.
A portable MCP server that scrapes SPA/JS-rendered webpages and extracts structured API endpoint data. It uses headless Chromium to render JavaScript and provides tools for scraping, endpoint extraction, screenshots, and database seeding.
Converts web pages and HTML strings into clean, LLM-optimized Markdown with metadata extraction and token estimation. It uses a lightweight, browserless approach to provide token-efficient output for more effective LLM processing.
Browser automation MCP server that uses a real browser to give agents eyes and hands—open pages, click, fill, screenshot, and run scripts via accessibility-tree snapshots.
Extracts and transforms webpage content into clean, LLM-optimized Markdown. Returns article title, main content, excerpt, byline and site name. Uses Mozilla's Readability algorithm to remove ads, navigation, footers and non-essential elements while preserving the core content structure.