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    Search and retrieve news articles and trending keywords from Google News and Google Trends. Summarize articles and extract keywords using optional NLP and LLM Sampling to get concise insights.
    5
    89
    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.
    4
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    MIT
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    Enables LLMs to interact with Fathom.video API for managing meeting recordings, retrieving transcripts and AI-generated summaries, searching meeting content, and accessing analytics and team data.
    10
    15 npm
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    MIT
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    Integrates Vale prose linting into AI coding assistants, enabling users to check text files for style and grammar issues using Vale's powerful linting engine. Provides automated style feedback with smart configuration discovery and rich formatted results.
    3
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    MIT
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    Provides MCP-compatible AI clients with offline text analysis and rewriting tools, including statistics, extractive summaries, keywords, readability scores, case conversion, entity extraction, and diffing, all running locally without API keys or network calls.
    7
    MIT
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    Enables AI agents and MCP clients to browse Roomtone meeting notes, add YouTube or pasted-text sources, generate summaries, ask questions answered from transcripts, and retrieve raw transcript text. Recording itself stays in the Roomtone app, so the server only reads and adds to existing meetings.
    7
    18 npm
    MIT
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    Turns plain text or Markdown, web pages, and local PDFs into editable Markdown outlines that can be rendered as standalone, offline-capable interactive HTML mind maps. Works with any MCP client with no API key required, since the connected model writes the final outline from a draft and cleaned source text.
    4
    MIT
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    Unofficial MCP server for working with Kagi without API access (you'll need to be a customer, tho). Searches and summarizes. Uses Kagi session token for easy authentication.
    2
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    MIT
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    MCP Long Context Reader is a Python-based toolkit designed to overcome the context window limitations and high costs associated with Large Language Models (LLMs) processing extensive documents. It provides a FastMCP server with multiple, powerful strategies for an LLM agent to 'read' and query long documents without needing to load the entire text into its context window.
    5
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    MIT
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    Enables users to extract and review Claude's plan reasoning in Claude Code by reading plan files and providing a structured template for decisions, tradeoffs, and assumptions.
    1
    15 npm
    MIT
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    Enables agents to check and retrieve concept-structured YouTube video summaries from the oratilo library via lookup and full-text search tools, avoiding redundant summarization work.
    2
    MIT
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    Delegates replaceable grunt work (boilerplate, formatting, translation, long-document summarizing) from a premium agent to cheap models behind a local LiteLLM proxy, auto-routing each task by type. Delegated calls run in a separate process, so the subscription session and the API credentials never share an environment.
    3
    26 PyPI
    1
    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.
    19
    48
    MIT