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    A small MCP server that gives agents rich context about a YouTube video — its transcript, jump-to-the-moment deep links, metadata, and most-replayed moments — so they can answer questions, summarize, pull quotes, or surface highlights.
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    MIT
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    A FastMCP server that enables AI assistants to extract structured information from unstructured text using Google's langextract library through a secure, optimized Model Context Protocol interface.
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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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    Provides MCP tools for querying and summarizing Northwest A&F University campus information, including trending QQ channel posts, official website notices/events/competitions, and cross-site custom searches with Markdown output and source links.
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    MIT
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    distill-mcp-v2 is a high-performance, network-dependency-free Python FastMCP server designed to aggressively optimize Large Language Model (LLM) context windows. It provides specialized tools for compressing and analyzing massive AI-agent payloads without losing critical semantic information.
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    MIT
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    A Node.js implementation of the Kagi Model Context Protocol server that enables Claude AI to search the web and summarize documents, videos, and audio using Kagi's APIs.
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    MIT
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    An MCP server for managing and persisting notes, offering CRUD operations, note summarization, and resource-based access via a note:// URI scheme.
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    MIT
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    A simple note storage and management system that allows users to add, access, and summarize notes through a custom URI scheme. Supports creating summaries with configurable detail levels and provides real-time resource change notifications.
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