data-scraper-agent

To automate scraping public data and store it in Notion, you need a workflow that collects items from your sources, deduplicates them by URL, and writes the results directly to your Notion database. This process removes the manual effort of hand-copying results by automatically sending collected public data to your storage target.

Yes, you can use GitHub Actions to schedule a web scraping job for recurring execution. This approach handles the scheduled execution of your data collection agents, ensuring your tracking workflows for jobs, prices, or news run automatically without managing separate infrastructure.

The best way to filter and enrich scraped RSS feeds is to batch the collected items through Gemini for AI-driven scoring, summarization, and classification. This enrichment process automatically flags the most relevant items from your public data sources before storing them.

Yes, this data collection approach works with JavaScript-rendered pages, alongside standard websites, APIs, and RSS feeds. Multi-source collection supports scraping dynamic web content, allowing you to monitor complex public data sources that require rendering before extraction.

To prevent duplicate entries when tracking public data sources, the automated agent applies URL deduplication before writing to storage. This ensures that only new items are added to your Notion, Sheets, or Supabase databases during recurring scheduled executions.

You can integrate an automated scraping agent with Notion, Google Sheets, or Supabase for reliable storage. These storage integrations receive the collected, deduplicated, and Gemini-enriched public data directly from your scheduled tracking workflows.