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TrendRadar

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GitHub Python GPL-3.0

Description

AI-driven public opinion and trend monitor with multi-platform aggregation, RSS subscriptions, smart keyword filtering, AI-powered news analysis and briefings, supporting MCP integration and push notifications via WeChat, Feishu, DingTalk, Telegram and more.

Key Features

  • Multi-platform trend aggregation — real-time scraping from 30+ sources covering tech, finance, social media
  • AI-powered smart filtering — LLM-driven news summarization and intelligent filtering to auto-exclude irrelevant content
  • Multi-channel push notifications — supports WeChat Work, personal WeChat, Telegram, DingTalk, Feishu, Slack and 10+ channels
  • MCP architecture support — integrates with AI assistants via Model Context Protocol for intelligent Q&A
  • One-click Docker deployment — deploy in 30 seconds with GitHub Actions automation and GitHub Pages static hosting
  • RSS feed management — custom RSS source subscriptions with keyword filtering and scheduled updates

Use Cases

💡 Personal news assistant: auto-aggregate and filter news of interest, push daily digests to WeChat or Telegram
💡 Industry trend monitoring: track dynamics of specific industries or competitors for timely intelligence
💡 Tech trend tracking: monitor GitHub Trending, Hacker News and other platforms to stay ahead of tech developments
💡 Enterprise internal intelligence: customize information sources for teams, push industry briefings via Feishu or DingTalk
💡 Social media monitoring: real-time tracking of trending topics and public sentiment on social platforms

Strengths & Limitations

✅ Strengths

  • • High community interest (62.0k stars)
  • • Responsive to issues, low backlog

⚠️ Limitations

  • • Restrictive license (GPL-3.0)

Tags

automation llm python tools mcp web

Categories

🔄 Workflow 📚 RAG Tools

Quick Start

# Clone the project
git clone https://github.com/sansan0/TrendRadar.git
cd TrendRadar

# Option 1: Docker deployment
docker compose up -d

# Option 2: GitHub Actions (Fork and configure Secrets in Settings)
# Auto-runs after pushing to main branch

# Run locally
pip install -r requirements.txt
python main.py
Visit GitHub

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