Quick overview
This workflow runs twice daily to collect top stories from Hacker News, latest articles from TechCrunch RSS, and US YouTube Science & Technology trending videos, then stores normalized results in an n8n Data Table for use by downstream widget/webhook workflows.
How it works
- Runs on a schedule at midnight and 8am (server time).
- Deletes any existing rows in the n8n Data Table for today’s date to avoid duplicates.
- Fetches the current top story IDs from the Hacker News API, loads details for the top 20, and normalizes them into date/source/title/url/score/rank rows.
- Reads the TechCrunch RSS feed, keeps the first 15 items, and normalizes them into the same schema (with score set to 0).
- Calls the YouTube Data API v3 to retrieve the top 15 US “mostPopular” videos in category 28 and normalizes them with viewCount as the score.
- Inserts the normalized rows from Hacker News, TechCrunch, and YouTube into the n8n Data Table.
Setup
- Create an n8n Data Table named
tech_trends with columns: date (string), source (string), title (string), url (string), score (number), and rank (number).
- Create a Google Cloud API key with the YouTube Data API v3 enabled and add an n8n HTTP Query Auth credential that sends it as the
key query parameter.
- Select that HTTP Query Auth credential in the YouTube request step and adjust the schedule times/timezone if needed.
Requirements
- Serve Tech Trends via JSON Webhook for Desktop Widgets (Requires Collector) + Stream Tech Trends to SwiftBar macOS Menu Bar via n8n Webhook (Requires Collector)
Customization
- Google Cloud API key with the YouTube Data API v3 (free)