{"id":"trendradar","name":"TrendRadar","homepage":"https://github.com/sansan0/TrendRadar","repo_url":"https://github.com/sansan0/TrendRadar","category":"ai-tools","subcategories":["trend-monitoring","social-listening","news-aggregation"],"tags":["trends","mcp","social-media","rss","ai-analysis","sentiment","notifications","docker"],"what_it_does":"An AI-driven trend monitoring platform that aggregates public opinion from multiple social and news sources, applies AI analysis (sentiment, summaries, predictions), and delivers structured notifications via 9 channels including Telegram, Slack, and WeChat.","use_cases":["Real-time monitoring of trending topics across social media and news for brand or topic intelligence","AI-summarized trend reports with sentiment analysis delivered on a schedule","RSS feed aggregation with keyword filtering to reduce information overload","MCP-enabled natural language trend queries for AI agent workflows","Multi-language trend monitoring with AI-powered translation"],"not_for":["Deep social media analytics requiring historical data export or raw data access","Enterprise compliance monitoring requiring certified data provenance","Platforms needing guaranteed data completeness (dependent on public source availability)"],"best_when":"You want a self-hosted, lightweight trend intelligence system that can push AI-analyzed summaries to messaging apps and also expose trend data to AI agents via MCP.","avoid_when":"You need enterprise-grade social listening with SLAs (e.g., Brandwatch, Sprinklr), or require raw data access for custom analytics.","alternatives":["Brandwatch","Mention.com","Google Alerts + manual","Feedly","Perplexity Spaces"],"af_score":59.1,"security_score":55.0,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"v6.0.0","last_evaluated":"2026-03-01T09:50:06.311627+00:00","performance":{"latency_p50_ms":null,"latency_p99_ms":null,"uptime_sla_percent":null,"rate_limits":null,"data_source":"llm_estimated","measured_on":null}}