Trendradar — AI Agent Framework: Live Stats & TrendScore

Live GitHub stats, community sentiment, and trend data for Trendradar. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Jun 19, 2026 • Sentiment updated: Jun 29, 2026

GitHub Statistics

Community Sentiment

Community Buzz: TrendRadar is a sharp framework for surfacing emerging tools and trends — and I'm guessing your users often need to *pick* which tool to actually deploy for a given workflow or use case from GitHub

Pros & Cons

What People Love

TrendRadar's ability to surface emerging tools and trends from GitHub, DEV.to users praise its potential

Common Complaints

RSS translation issues

Biggest Positive: TrendRadar helps

Biggest Negative: RSS translation issues

Why Trendradar Stands Out

TrendRadar stands out from other news aggregation tools with its AI-driven approach to news analysis and trending topic detection. Its ability to integrate with multiple platforms, including social media and messaging apps, makes it a unique solution for users looking to stay informed. Additionally, TrendRadar's use of natural language processing and machine learning algorithms enables it to provide more accurate and relevant news recommendations. By leveraging these technologies, TrendRadar solves the problem of information overload and provides users with a personalized news feed that meets their specific needs.

Built With

Build a real-time news aggregator — TrendRadar's multi-platform aggregation and smart alerts enable users to stay up-to-date with the latest news, Build a trending topic detector — TrendRadar's AI-driven analysis and natural language processing capabilities help identify trending topics, Build a personalized news feed — TrendRadar's keyword-based filtering and AI-powered news selection enable users to receive relevant news, Build a social media monitoring tool — TrendRadar's integration with various social media platforms and messaging apps allows for real-time monitoring, Build a data analysis dashboard — TrendRadar's data aggregation and visualization capabilities enable users to gain insights from large datasets

Getting Started

  1. Install TrendRadar using the command `pip install trendradar`
  2. Configure your TrendRadar instance by running `trendradar config` and following the prompts
  3. Add your social media and messaging app accounts to TrendRadar using the `trendradar accounts` command
  4. Customize your news feed by using the `trendradar filters` command to set up keyword-based filtering
  5. Try running `trendradar dashboard` to verify that your instance is working correctly and view your personalized news feed

About

⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。

Official site: https://sansan0.github.io/TrendRadar/

Category & Tags

Category: social

Tags: ai, bark, data-analysis, docker, hot-news, llm, mail, mcp, mcp-server, news, ntfy, python, rss, trending-topics, wechat, wework

Market Context

Competitive positioning in AI trend analysis