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"Exploring the word 'Make' and its possible applications" matching MCP servers:

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    A Model Context Protocol server that provides tools for analyzing text documents, including counting words and characters. This server helps LLMs perform text analysis tasks by exposing simple document statistics functionality.
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    Apache 2.0
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    Enables exploring Steam store reviews and community discussion threads with server-side filtering, temporal analysis, and metadata context for understanding player sentiment and feedback beyond store page noise.
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    BSD 3-Clause
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    ✨ 为你的 AI 助手装上 B 站的眼睛:一键提取视频字幕与热门评论,助力高效信息总结 🚀 ✨ Equip your AI assistant with "Bilibili Eyes": One-click extraction of video subtitles and popular comments for efficient information summarization 🚀
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    GPL 3.0
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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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    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.
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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.
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    MIT
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    Provides 14+ character-level text analysis tools that give LLMs the ability to accurately count letters, analyze individual characters, and work with text at the character level—overcoming tokenization limitations.
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    MIT
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    A Python MCP server for fetching and summarizing news articles from the Boring News API by date, category, tags, people, and similarity.
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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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    Fetches and processes Hacker News discussions to prepare them for Claude to generate high-quality summaries, handling comment structure and metadata to help Claude understand the relative importance of different comments.
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    MIT
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    The URL-Context-MCP MCP Server provides a tool to analyze and summarize the content of URLs using Google Gemini's URL Context capability via the Gemini API. Now also supports optional grounding with Google Search alongside URL Context. The server is designed to follow prompt-only orchestration: con
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    MIT
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    This server enables users to store, manage, and summarize notes using a custom URI scheme, with functionality to add new notes and generate summaries with varying levels of detail.
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