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    Enables AI-powered web browsing automation using Google's Gemini 2.5 Computer Use API. Allows agents to navigate websites, click buttons, fill forms, and extract information through natural language commands with real-time progress tracking.
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    7
    MIT
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    Context-efficient MCP server for AI agents. fetch_extract reduces token usage by a median 98.1% (53,820 → 2,001 tokens) vs raw HTML — saves ~$0.156/call at Sonnet pricing. Pay $0.02 USDC on Base via x402. First call free per wallet. 10 always-free utility tools included.
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    An MCP server that provides web_search and web_fetch tools returning plain text via the tbro terminal browser to reduce token usage, with the trade-off of no JavaScript support.
    Last updated
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    MIT
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    An MCP (Model Context Protocol) server that gives AI agents live, structured ad intelligence across Facebook, Google, and Instagram — data that no base model can produce from training alone. Powered by Apify actors. Works with any MCP-compatible client: Cursor, Claude, etc.
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    Checks username availability and retrieves account information across major social media platforms including YouTube, TikTok, Threads, X (Twitter), and Instagram, perfect for brand name qualification and competitive research.
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    MIT
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    Enables web searching via DuckDuckGo and page fetching with automatic HTML-to-Markdown conversion to reduce LLM token usage by approximately 60%. It provides tools for search, content extraction, and combined operations without requiring any external API keys.
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    An MCP server that enables users to search and navigate Madison, Wisconsin municipal ordinances using a TF-IDF search index. It provides specific code sections and citations to answer questions about local regulations like building permits and zoning.
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    Enables web content scanning and analysis by fetching, analyzing, and extracting information from web pages using tools like page fetching, link extraction, site crawling, and more.
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    MIT
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    Unofficial MCP server wrapping crawl4ai that enables extraction and analysis of content from web pages, PDFs, Office documents, YouTube videos, and more, with AI-powered summarization and Google search integration to reduce token usage while preserving key information.
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    MIT
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    Refined MCP server for GitHub GraphQL API. GitHub's official MCP Server exposes dozens of low-level tools that bloat token usage and are mostly impractical for LLMs. gh-mcp achieves the best of both worlds by providing a single, powerful interface: GitHub GraphQL, wrapped with smart abstractions.
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    Load and parse webpages using natural language queries to extract structured data. Manage browser sessions for interactive automation and retrieve usage metrics.
    Last updated
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    MIT