data-scraper-agent

You can automate web scraping and store results in Notion by using Python requests and BeautifulSoup to collect public data, then mapping the processed results directly into Notion databases via the Notion API for research or tracking.

Yes, you can enrich scraped data by passing the collected public information to AI models like the Gemini API. The system uses AI to automatically summarize, classify, or score the raw data for enhanced market analysis insights.

Yes, this scraping approach effectively monitors prices and job boards by continuously collecting data from websites, APIs, or feeds. It tracks e-commerce prices and job postings, then automatically stores results in Sheets or Supabase.

To scrape and process public data, you need Python libraries including requests for fetching URLs, beautifulsoup4 and lxml for parsing HTML or XML, python-dotenv for environment variables, and pyyaml for configuration management.

BeautifulSoup is limited to parsing static HTML and XML from public sources, meaning it cannot execute JavaScript or interact with dynamically rendered content. For highly interactive or restricted websites, additional browser automation tools may be required.