ScriptsApr 9, 2026·3 min read

TrendRadar — AI-Driven Trend Monitoring System

Deploy an AI-powered trend monitoring system in 30 seconds. Aggregates from 50+ platforms, AI-filters by your interests, pushes to WeChat/Telegram/Slack/email. GPL-3.0, 51K+ stars.

AI
AI Open Source · Community
Quick Use

Use it first, then decide how deep to go

This block should tell both the user and the agent what to copy, install, and apply first.

  1. Deploy with Docker:
docker run -d --name trendradar 
  -p 8080:8080 
  sansan0/trendradar:latest

  1. Open http://localhost:8080 and configure your interests and notification channels.

  2. TrendRadar starts collecting and filtering trending content automatically.

Intro

TrendRadar is an AI-driven public opinion and trend monitoring system with 51,000+ GitHub stars. It aggregates trending content from 50+ platforms and RSS feeds, applies AI-powered intelligent filtering based on your interests, and delivers curated alerts to 9+ channels including WeChat, Telegram, Slack, and email. Deployable in 30 seconds via Docker. Best for developers, marketers, and researchers who need to stay on top of industry trends without manual browsing. Works with MCP for AI assistant integration.

Explore more open-source AI tools on TokRepo AI Open Source.

TrendRadar — AI-Driven Public Opinion & Trend Monitoring

What It Does

TrendRadar continuously monitors trending topics across multiple platforms, uses AI to filter content matching your interests, translates foreign content automatically, and pushes curated summaries to your preferred notification channels — all on autopilot.

Key Features

  • Multi-platform aggregation — monitors 50+ platforms and custom RSS feeds
  • AI intelligent filtering — describe your interests in natural language, AI selects relevant content
  • Automated translation — AI-powered translation for cross-language monitoring
  • 9+ notification channels — WeChat, Telegram, Feishu, DingTalk, Slack, email, and more
  • Timeline scheduling — control collection, analysis, and delivery timing
  • MCP integration — connect to AI assistants via Model Context Protocol
  • Visual config editor — GUI for managing all settings
  • 30-second deploy — Docker one-liner to get started

Installation Options

Docker (recommended):

docker run -d --name trendradar 
  -p 8080:8080 
  sansan0/trendradar:latest

Shell script (macOS):

curl -fsSL https://raw.githubusercontent.com/sansan0/TrendRadar/main/install.sh | bash

Python:

git clone https://github.com/sansan0/TrendRadar.git
cd TrendRadar
pip install -r requirements.txt
python main.py

Use Cases

  1. Tech trend monitoring — track GitHub trending, Hacker News, Reddit for your tech stack
  2. Competitor intelligence — monitor mentions of competitors across platforms
  3. Research alerts — get notified about new papers and breakthroughs in your field
  4. Social media monitoring — track brand mentions and industry discussions
  5. News aggregation — curated daily/weekly digest of relevant news

Configuration Example

Describe your interests in natural language:

I'm interested in AI coding tools, MCP servers, Claude Code updates,
and open-source AI infrastructure. Ignore cryptocurrency and gaming news.

TrendRadar's AI filters all incoming content based on this description.

FAQ

Q: What is TrendRadar? A: TrendRadar is an open-source AI-driven trend monitoring system that aggregates content from 50+ platforms, intelligently filters it based on your interests, and delivers curated alerts to your preferred channels.

Q: Is TrendRadar free? A: Yes, TrendRadar is free and open-source under the GPL-3.0 license. Self-hosted, no subscription required.

Q: How fast can I deploy TrendRadar? A: With Docker, deployment takes about 30 seconds. The shell script installer takes about 2 minutes.

🙏

Source & Thanks

Created by sansan0. Licensed under GPL-3.0.

TrendRadar — ⭐ 51,000+

Thanks to sansan0 for building a comprehensive trend monitoring tool that saves hours of manual browsing.

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