TrendRadar
A real-time hotspot monitoring and news aggregation assistant that provides AI-powered analysis of trending topics across multiple platforms via the Model Context Protocol. It enables users to track news and receive automated notifications through va
What is TrendRadar?
TrendRadar is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to real-time hotspot monitoring and news aggregation assistant that provides ai-powered analysis of trending topics across multiple platforms via the model context protocol. it enables users to track new...
A real-time hotspot monitoring and news aggregation assistant that provides AI-powered analysis of trending topics across multiple platforms via the Model Context Protocol. It enables users to track news and receive automated notifications through va
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- A real-time hotspot monitoring and news aggregation assistan
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx trendradarConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use TrendRadar
TrendRadar is a real-time news aggregation and hotspot monitoring system that tracks trending topics across 35+ Chinese social platforms including Douyin, Zhihu, and Bilibili. It exposes 14 MCP tools for AI-powered analysis — covering topic trend detection, sentiment analysis, cross-platform comparison, and automated summary generation. Teams and researchers use it to monitor breaking news, analyze information heat changes over time, and receive automated push notifications via Telegram, Feishu, Slack, or iOS Bark.
Prerequisites
- Docker and Docker Compose installed (recommended deployment method)
- Python 3.8+ (for local non-Docker setup)
- At least one notification channel configured (Telegram bot token, Feishu webhook, Slack webhook, or Bark URL)
- An MCP client such as Claude Desktop or Cursor
Clone the TrendRadar repository
Clone the repository from GitHub. Note the canonical source is at github.com/sansan0/TrendRadar.
git clone https://github.com/sansan0/TrendRadar.git
cd TrendRadarConfigure environment variables
Copy the example config file and set your notification channels and crawler options. At minimum configure REPORT_MODE and at least one push notification destination.
cp .env.example .env
# Edit .env and set:
# REPORT_MODE=daily # Options: daily, incremental, current
# ENABLE_CRAWLER=true
# TELEGRAM_BOT_TOKEN=your-bot-token
# TELEGRAM_CHAT_ID=your-chat-id
# FEISHU_WEBHOOK_URL=https://open.feishu.cn/open-apis/bot/v2/hook/...
# SLACK_WEBHOOK_URL=https://hooks.slack.com/services/...
# BARK_URL=https://api.day.app/your-device-key/Start TrendRadar with Docker Compose
Pull the latest images and start the service in detached mode. The crawler will begin collecting trending topics immediately.
docker compose pull
docker compose up -dVerify the service is running
Check that the containers are healthy and data collection has started. The MCP server listens on HTTP for tool calls from your AI client.
docker compose ps
docker compose logs -f trendradarConfigure the MCP server in your AI client
Add TrendRadar to your Claude Desktop or other MCP client configuration so your AI assistant can call the 14 analysis tools.
TrendRadar Examples
Client configuration
Add TrendRadar's MCP server to your Claude Desktop configuration. The service runs locally via Docker on port 8080 by default.
{
"mcpServers": {
"trendradar": {
"command": "docker",
"args": ["exec", "-i", "trendradar", "python", "-m", "trendradar.mcp_server"],
"env": {}
}
}
}Prompts to try
Use these prompts with TrendRadar connected to explore trending topics and trend analysis.
- "What are the top trending topics on Chinese social media right now?"
- "Search for news about Bitcoin from the last 3 days and analyze the trend"
- "Compare how Zhihu and Weibo are covering AI developments this week"
- "Generate a summary report of today's hottest news topics"
- "Analyze the sentiment of coverage around the latest tech news"Troubleshooting TrendRadar
No trending data appears after startup
Ensure ENABLE_CRAWLER=true is set in your .env file and the crawler container is running. Check logs with 'docker compose logs crawler' to see if any platform scrapers are returning errors.
Push notifications are not being delivered
Verify your webhook URLs and tokens are correctly formatted in .env. For Telegram, confirm your bot has permission to post to the specified TELEGRAM_CHAT_ID. For Feishu, test the webhook URL with a curl POST first.
MCP tools return empty results for date-based queries
TrendRadar stores data locally as it crawls. Queries for historical dates only work after the crawler has run long enough to accumulate data for those dates. Use get_system_status to confirm crawl history.
Frequently Asked Questions about TrendRadar
What is TrendRadar?
TrendRadar is a Model Context Protocol (MCP) server that real-time hotspot monitoring and news aggregation assistant that provides ai-powered analysis of trending topics across multiple platforms via the model context protocol. it enables users to track news and receive automated notifications through va It connects AI assistants to external tools and data sources through a standardized interface.
How do I install TrendRadar?
Follow the installation instructions on the TrendRadar GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with TrendRadar?
TrendRadar works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is TrendRadar free to use?
Yes, TrendRadar is open source and available under the GPL 3.0 license. You can use it freely in both personal and commercial projects.
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Set Up TrendRadar in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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