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TrendRadar

by xhh-im
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Python
Hybrid

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    • TrendRadar

      YangLang116
      A
      license
      A
      quality
      D
      maintenance
      A lightweight hotspot news assistant that aggregates trending information from multiple platforms for AI-powered monitoring and analysis. It supports the Model Context Protocol to provide intelligent news filtering and summarized insights through integrated AI clients.
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    • TrendRadar

      LeePresident
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      license
      A
      quality
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    • TrendRadar

      lizouzt
      A
      license
      A
      quality
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      A real-time news and hot spot aggregation server that monitors multiple platforms like Weibo, Zhihu, and Bilibili. It enables AI assistants to fetch, filter, and analyze trending topics through the Model Context Protocol for personalized information tracking.
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    • TrendRadar

      funinii
      A
      license
      A
      quality
      D
      maintenance
      TrendRadar aggregates hot news from multiple platforms and provides AI-powered trend analysis via the Model Context Protocol. It enables users to filter for relevant information and receive automated updates across various notification channels like Telegram, Slack, and WeChat.
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    • trendradar-mcp

      iPythoning
      A
      license
      A
      quality
      B
      maintenance
      Provides an AI-powered news aggregation and trend monitoring service, enabling multi-platform hotspot aggregation, RSS subscriptions, keyword filtering, AI translation, analysis briefs, and smart alerts delivered to various channels, all accessible through natural language via MCP.
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    Deploy Server
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    TDQS

    A3.9/5.0

    Scored across 14 tools

    Disambiguation4/5

    Most tools have distinct purposes. Potential overlap between analyze_sentiment and analyze_topic_trend (both analyze topics) but they focus on different aspects (sentiment vs. lifecycle/viral/predict). Overlap between get_latest_news and get_news_by_date is clarified by descriptions. Overall, boundaries are clear.

    Naming Consistency4/5

    All tools use snake_case with a consistent verb_noun pattern (e.g., analyze_sentiment, search_news). A few exceptions like get_news_by_date (includes preposition) and search_related_news_history (longer) break the pattern slightly, but the naming is largely predictable and readable.

    Tool Count5/5

    14 tools is well-scoped for a trend analysis and news retrieval server. The number covers data retrieval, analysis, reporting, configuration, and system management without being excessive or sparse.

    Completeness4/5

    The tool surface covers core operations: news retrieval (multiple methods), analysis (sentiment, trends, insights), reporting, and system status. Missing are tools to modify configuration (e.g., update keywords or platforms) or manage data (create/update/delete), but these are not essential for the consumption-oriented domain.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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