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alisen39

WhatsHot

by alisen39
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Python
Hybrid

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Alternatives to WhatsHot

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    Related Servers

    • whatshot-mcp

      RayLLLU
      F
      license
      A
      quality
      C
      maintenance
      MCP server for WhatsHot API providing read-only access to aggregated hotlists, news flashes, and gold prices, with tools to fetch current data, query history, search, and get trends.
      7
      1
      -

    • Daily Hots MCP

      fancyboi999
      A
      license
      Not graded
      quality
      D
      maintenance
      A Python-based MCP server that aggregates real-time trending topics and news from over 30 sources including social media, technology, and finance platforms. It enables AI applications to retrieve the latest hot searches and news from major services like Weibo, Baidu, and IT Home through a unified interface.
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    • TrendRadar

      SsdSalesman
      A
      license
      A
      quality
      D
      maintenance
      An aggregator for real-time hot topics and news from major social and financial platforms like Zhihu, Bilibili, and Wall Street News. It features an MCP server that allows AI models to fetch and analyze trending information for automated insights.
      17
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    • MCP Hot News Server

      wudalu
      A
      license
      Not graded
      quality
      D
      maintenance
      A modern multi-platform hot news aggregation server based on FastMCP that supports real-time hot topics data collection from 13+ major platforms including Zhihu, Weibo, Baidu, and Bilibili.
      3
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    • whatshot-mcp

      alisen39
      A
      license
      Not graded
      quality
      B
      maintenance
      MCP server that connects to a WhatsHot Backend over HTTP to provide hot topic discovery, trend analysis, and historical data tools such as current hotlists, trend series, and event analysis.
      MIT
    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.4/5.0

    Scored across 7 tools

    Disambiguation4/5

    Each tool targets a distinct concern: source discovery, schema introspection, live fetching, history querying, searching, trend analysis, and storage stats. The main potential confusion is between query_history and search_history, but the descriptions make clear that querying returns persisted items with pagination while searching targets content and returns attributable evidence, which differentiates them sufficiently.

    Naming Consistency4/5

    Names mostly follow a verb_noun pattern with clear action prefixes (list_, get_, fetch_, query_, search_, get_). There's a minor deviation with get_source_schema vs fetch_current where 'fetch' and 'get' use different verbs for similar acquisition actions, but this is arguably intentional given that fetch_current accesses the network while get_source_schema is local.

    Tool Count5/5

    Seven tools is within the ideal 3-15 range and each tool appears to earn its place by covering a distinct dimension of the domain: discovery, introspection, live fetch, history retrieval, search, analytics, and storage management. No redundant or filler tools.

    Completeness4/5

    The surface covers the full lifecycle: source discovery, schema understanding, live fetching, persistence querying, search, trend analytics, and storage management. Minor gaps exist—such as the absence of explicit history write/capture control (though fetch_current implies an upstream capture mechanism) and possibly pagination/sampling controls for trend series—but no obvious dead ends that would cause agent failures.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

    Resources