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    A comprehensive web scraping server that transforms web content into clean, agent-ready Markdown with automatic citations and efficient caching. It features a robust suite of tools for metadata extraction, sentiment analysis, SEO auditing, and security scanning while strictly adhering to robots.txt policies.
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    MIT
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    This application is a powerful browser monitoring and interaction tool that enables AI-powered applications via Anthropic's Model Context Protocol (MCP) to capture and analyze browser data through a Chrome extension.
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    MIT
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    Reliable, scalable browser infrastructure for AI agents. Route, pool, and failover across any browser provider. 8 built-in browser tools using raw Chrome CDP - navigate, screenshot, snapshot, interact, evaluate. Zero-config with auto Chrome detection & concurrent sessions support
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    MIT
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    Agent-native browser control MCP server that enables AI agents to browse and interact with web pages via accessibility tree snapshots and ref ID-based commands.
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    MIT
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    touch-browser is an evidence-grounded MCP server for public docs and research web workflows. It helps AI agents search and open web pages, extract page-local evidence with citations and confidence bands, classify browsing risk, and synthesize multi-page sessions into citation-ready reports.
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    Mozilla Public 2.0
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    A headless browser MCP server that allows AI agents to fetch web content and perform Google searches without API keys, supporting various output formats like Markdown, JSON, HTML, and text.
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    MIT
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    An open-source MCP server that provides browser automation capabilities to external AI systems, enabling navigation, DOM interaction, and web content extraction.
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    Apache 2.0
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    An MCP server for browser automation using Puppeteer that enables AI assistants to navigate web pages, interact with UI elements, and capture screenshots. It supports comprehensive web tasks including form filling, content extraction, and executing custom JavaScript within the browser context.
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    MIT