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    Enables an agent to run ten ready-made research and monitoring workflows — competitor digests, cited reports, paper alerts, market maps, regulatory and due-diligence watches — pulling from Firecrawl, Tavily, GitHub and landing results in Notion, Slack, Google Docs, Sheets and Linear. Fields are filed with the user's own keys held in the operating system keychain, and every action that creates, sends or changes anything is shown and approved first.
    21
    Apache 2.0
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    MCP server exposing 40 best-practice product management skills plus workflows and lifecycle tools, instantly accessible to any AI via Model Context Protocol.
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    21 npm
    21
    Apache 2.0
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    This project implements a Model Context Protocol (MCP) server providing Formula One racing data using the Python FastF1 library. Inspired by an existing TypeScript server, it offers similar F1 data functionalities natively in Python via FastF1.
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    MIT
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    Gives Claude read access to Google Analytics 4, Google Search Console, and Microsoft Clarity data, with connections stored once and reusable across projects.
    8
    MIT
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    Clinical research MCP server providing real-time access to PubMed (35M+ papers) and ClinicalTrials.gov (400K+ trials). Built for trial coordinators and life sciences teams. No API key required.
    3
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    MIT
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    Enables searching live job postings, aggregating labour-market slices, and reporting how long listings have been open, with filters for titles, location, salary, and more.
    4
    43 npm
    MIT
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    Enables AI clients to search, read, and accurately quote public-domain books from Project Gutenberg, with chapter detection and stable line numbers for citation. Its quote_check tool verifies whether a quotation actually appears in a book and reports how faithful the copy is.
    6
    161 npm
    MIT
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    Lets an AI assistant do everything you would do on Ancestry.com by hand: search records, read and edit trees (people, facts, sources, citations, notes, tags, media), review hints, attach records, look at DNA matches, and read or send messages.
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    MIT
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    Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.
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    AGPL 3.0
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    Enables AI assistants to search multiple tech job boards at once, summarize what the market is asking for, and rank postings by how well they match a user's own skills.
    5
    MIT
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    Returns USDA-derived edible yield, refuse percent and trim waste for 305 raw fruits and vegetables, letting an assistant convert between as-purchased and edible weights. It also answers how many whole items or how much produce to buy for a recipe amount given in grams, pounds, cups or household measures.
    4
    MIT
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    MCP server for the Internet Archive's Wayback Machine. Search archived snapshots, extract page text from a specific date, track how a site has changed over time, check if broken links are recoverable, and perform research across Internet Archive collections.
    6
    40 PyPI
    3
    MIT
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    This MCP server enables users to interact with and analyze the dair-ai/emotion dataset from Hugging Face containing labeled Twitter messages. It provides tools to sample data, search text, and perform statistical analysis on emotion distributions.
    4
    GPL 3.0
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    Enables agents to read an author's Microsoft CMT conference participation, submissions, statuses, and reviews, with change tracking and read-only access.
    6
    GPL 3.0
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    Enables MCP-capable chat hosts to analyze Pokémon Champions VGC doubles replays, evaluate teams against metagame snapshots, and run auditable damage calculations with local deterministic evidence.
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    Provides B2B positioning and messaging tools based on the IMPACT Framework, enabling analysis of champions, competitors, and value propositions to craft compelling messages and execute strategic audits.
    8
    43 npm
    MIT
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    Enables local evaluation and revision comparison of how audience attention, curiosity, surprise, understanding, fatigue and mixed emotions evolve through a creative work, based on time-ordered cue annotations rather than automatic media analysis. Also exposes audience-panel weighting, sensitivity checks, dataset inspection, calibration fitting/application and parameter tuning, all computed from supplied objects without external calls.
    10
    MIT
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    Enables MCP clients to query documented Sportmicro football endpoints for players, teams, matches, player statistics, and weekly/season projections through narrow, read-only, validated tools.
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    MIT