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    Enables agents to fetch app reviews from Apple's App Store and Google Play per country store, newest first, filtered by date or star rating, with each scheduled run returning only reviews not seen before. It also returns a per-app, per-country rating trend row with the current rating, rating count, change since the last run, and the star split of new reviews.
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    MIT
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    Enforces a marketing pre-flight: plan the campaign with kill criteria, score each offer on an explainable 0-100 rubric, and require every tactic to cite a scored offer plus a success metric before any spend.
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    42 npm
    MIT
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    Turns your AI host into a product videographer — scripted screen recordings of your own web app with a gliding cursor, camera zooms, highlight callouts, captions, and branded transitions, plus marketing-grade screenshots. Automatic dark-frame cleanup and MP4/GIF export. Free, MIT, 100% local — no account, no API keys.
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    42 npm
    3
    MIT
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    It enables solo builders to automatically log product changes to PostHog and later get statistically honest verdicts on whether those changes moved key metrics, without needing enough traffic for A/B tests.
    2
    6 npm
    MIT
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    Pre-build reality check for AI coding agents. Scans GitHub, Hacker News, npm, PyPI & Product Hunt in parallel — returns a 0-100 reality signal with real competitor data.
    1
    88 PyPI
    827
    MIT
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    Enables discovery of a company's public feature board (Canny, Featurebase, Frill, UserVoice, Productboard) from its domain and retrieval of its most-voted requests with votes, status, comments, and the integrations customers ask for. Supports monitoring runs that surface only new requests, status changes, and vote jumps since a prior run using a saved state key.
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    280 npm
    MIT
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    Enables AI assistants to identify and quantify value leaks in organizations using Melt's methodology, providing structured estimates instead of generic vendor lists.
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    93 npm
    MIT
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    Enables agents to evaluate whether a product-adoption message is worth sending by applying a fixed, evidence-based rubric to a draft, recipient context, evidence, and the agent's own assessment, returning a send, revise, or hold recommendation with a score and reasons.
    2
    MIT
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    Competitive intelligence platform with 24 tools. Monitor competitor pricing, content, positioning, tech stacks, and AI visibility — track how ChatGPT, Claude, and Gemini rank your brand.
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    MIT
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    MCP server for AI agents providing 300 curated Japanese home & lifestyle products across 31 categories. Features mm-precision dimension search, related-item chains (1 product → 3-5 accessories), shelf+storage coordination, and Rakuten/Amazon affiliate links.
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    48 npm
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    MCP server for Drop Beacon (edc4me.com) — search and explore 80,000+ EDC products across 1,000+ brands. Track new drops, compare prices across retailers, check real-time stock availability, and analyze market trends for knives, flashlights, fidget toys, wallets, pens, and more.
    4
    100 npm
    MIT
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    Enables AI assistants to retrieve a Wildberries seller's product cards and customer reviews through the official Content and Feedbacks APIs.
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    72 npm
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    A hypothesis-driven B2B positioning engine with 8 tools for strategic positioning, competitive analysis, and go-to-market messaging.
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    52 npm
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    MIT
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    Connects AI coding tools to an Atono workspace, offering 41 tools to read and write stories, bugs, epics, subtasks, acceptance criteria, timeboxes, glossary, and AI context so agents work with real product knowledge.
    Apache 2.0