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    A Python-based MCP server adapted from the n8n_agent project that implements a note storage and summarization system. It enables users to create, retrieve, and summarize notes through the Model Context Protocol.
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    maintenance
    A universal MCP tool gateway that manages multiple remote tool processes, enabling LLMs to dynamically invoke web scraping, summarization, and knowledge retrieval through standardized Function Calling.
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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.
    7
    3
    MIT
  • A
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    tooltrim reduces the tokens agents spend re-reading bloated tool results. Run it as an MCP server exposing compress and expand_tool_output, or as a gateway in front of any upstream MCP server: it re-exposes the upstream tools unchanged and shrinks each result (HTML/JSON/logs/tables) before it reaches the model, keeping the relevant content only.
    2
    2
    MIT
  • A
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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.
    4
    33
    MIT
  • A
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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.
    19
    46
    MIT
  • A
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    Analyzes YouTube videos using Google's Gemini API, allowing users to get summaries or ask questions about video content via direct URL input.
    5
    19 npm
    2
    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.
    4
    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.
    8
    MIT