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    An MCP server for accelerator programs to query, review, and manage startup applications via natural language. It enables searching applications by sector or impact score, fetching full application details with reviewer notes, listing pending reviews, and flagging applications for panel discussion.
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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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    Enables read-only queries across App Store Connect and Google Play from one toolset, letting users list apps, track release states, and review merged store feedback without extra dependencies or credentials in demo mode.
    5
    46 npm
    MIT
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    A Python MCP server that gives Claude access to PM workflow data such as sprints, roadmap, blockers, and workload, using synthetic fixture data (no API keys required) and can be forked for real Linear/Jira integration.
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    Enables natural language control of OmniPlan 4 on macOS, allowing creation and manipulation of tasks, resources, dependencies, and project metadata through MCP-compatible agents.
    22
    26 PyPI
    1
    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.
    15
    48 npm
    1
    MIT
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    Mines public App Store and Steam reviews to surface the complaints, rating drops per version, and common pain points across one app or a set of competitors, with no API keys required. Enables natural-language comparison of up to eight apps or games by country and category so users can spot product opportunities and gaps.
    4
    26 PyPI
    MIT
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    Lets AI assistants query a live feedback collection database in plain language, retrieving entry counts broken down by type and classification status, and listing individual submissions filtered by type, urgency, or sentiment. Access is read-only and privacy-preserving, so answers can be produced without exposing submitter email addresses.
    2
    MIT
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    Enables AI assistants to manage Customer Thermometer surveys, including listing thermometers and recipient lists, adding or unsubscribing recipients, sending email surveys, and retrieving NPS, happiness, response, and comment reports.
    10
    Apache 2.0
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    Enables agents to create and drive instrumented Design Thinking sessions, inspect the append-only journal, and retrieve dossiers and handoff specs through MCP tools and resources.
    14
    Apache 2.0
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    Guides product design through mandatory phases—discovery, definition, prioritization, flows, and verification—so an AI assistant can run a project from problem to verified scope, with strict or free progression modes.
    36
    2,067 npm
    3
    MIT
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    Enables goal-driven plan simplification by tracing each step's necessity, detecting cycles, broken links, and transitive waste, and classifying items as required or pointless with review and recheck capabilities.
    8
    Apache 2.0
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    Enables AI assistants to create and validate surveys, distribute them, read and tag responses, and generate reports or exports through a hosted Streamable HTTP MCP endpoint with API-key authentication.
    MIT