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  • A
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    quality
    B
    maintenance
    Enables AI agents to search and retrieve structured merchant data, check availability, manage bookings, and submit feedback against an open commerce registry with real restaurant data for LA, Hong Kong, and Tokyo.
    Apache 2.0
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    quality
    D
    maintenance
    An MCP server that enables AI clients to search open data from Nerima City, Tokyo, including public facilities, AED locations, shelters, and parks.
    1
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  • F
    license
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    quality
    D
    maintenance
    Enables LLMs to retrieve Tokyo Stock Exchange stock information and execute SQL queries on Databricks SQL warehouses, deployed as a Databricks App.
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  • A
    license
    A
    quality
    D
    maintenance
    Provides comprehensive weather data (forecasts, historical, air quality, marine) from Open-Meteo through 12 tools, with support for single and batch location queries.
    12
    1
    Apache 2.0
  • A
    license
    A
    quality
    B
    maintenance
    Enables AI assistants to look up live weather data, including current conditions and up to 16-day forecasts, by converting place names to coordinates and fetching data from the Open-Meteo API without requiring an API key.
    3
    62 npm
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    Provides persistent memory for AI models by enabling the storage and retrieval of episodic, semantic, and procedural information through the memro protocol. It allows assistants to maintain long-term context via semantic search and chronological memory management.
    1
    MIT
  • A
    license
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    B
    maintenance
    Home Services MCP by HireNimbus lets AI agents find, compare, and book verified local pros for handyman, renovation, HVAC, plumbing, electrical, and landscaping jobs in supported US metro markets.
    Apache 2.0
  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables candy-store expansion planning and supplier forecasting across metro Atlanta's ten counties and 1,200 census tracts, modeling demand, heritage-segment specialty markets, competitor-aware capture, and distribution capacity. Users can locate optimal store sites under a budget, test what-if scenarios, and forecast weekly orders per center and category with p10/p90 ranges and expected losses.
    MIT