TrendRadar

This project targets the overload of news and public opinion data by aggregating multi-platform hot topics and RSS feeds, then applying AI-driven filtering, translation, and summarisation to deliver concise, relevant alerts. Unlike generic news aggregators, it integrates with multiple communication channels such as WeChat, Feishu, DingTalk, Telegram, email, ntfy, bark, and Slack, offering direct push notifications. It also supports MCP architecture for advanced natural language dialogue analysis, sentiment insight, and trend prediction. Its lightweight design and Docker support enable deployment within 30 seconds, appealing to ML/AI engineers needing rapid setup. With over 60,000 stars and recent commits, it shows active maintenance but no significant growth trend yet. It is not suitable when a team requires proprietary or enterprise-grade news monitoring with guaranteed data source SLAs or deeper customisation beyond the provided AI analysis and push integrations; in such cases, commercial platforms or specialised sentiment analysis tools might be preferable.

Choose this tool when you want a quick-to-deploy, AI-powered news and trend monitoring system that aggregates multiple platforms and pushes alerts to diverse communication channels. Consider alternatives like NewsNow or commercial sentiment analysis services if you need guaranteed data reliability, more granular customisation, or enterprise support.

This system fits teams building internal public opinion monitoring dashboards, AI-enhanced news briefing services, or automated trend alerting integrated into corporate chat tools. It is often used in setups requiring multi-platform data aggregation combined with AI summarisation and distributed push notifications.

Latest commit: 2026-07-17. Activity data is based on daily RepoPi snapshots of the GitHub repository.