Search, crawl, and scrape websites at scale.
Scrape a webpage and return content in Markdown format using Bright Data. Examples: scrape_as_markdown("https://example.com") -> "# Example Page Content..." scrape_as_markdown("https://news.ycombinator.com") -> "# Hacker News ..."
Search using Google, Bing, or Yandex with advanced parameters using Bright Data. Examples: search_engine("climate change") -> "# Search Results ## Climate Change - Wikipedia ..." search_engine("Python tutorials", engine="bing", num_results=5) -> "# Bing Results ..." search_engine("cats", search_type="images", country_code="us") -> "# Image Results ..."
Extract structured data from various websites like LinkedIn, Amazon, Instagram, etc. NEVER MADE UP LINKS - IF LINKS ARE NEEDED, EXECUTE search_engine FIRST. Supported source types: - amazon_product, amazon_product_reviews - linkedin_person_profile, linkedin_company_profile - zoominfo_company_profile - instagram_profiles, instagram_posts, instagram_reels, instagram_comments - facebook_posts, facebook_marketplace_listings, facebook_company_reviews - x_posts - zillow_properties_listing - booking_hotel_listings - youtube_videos Examples: web_data_feed("amazon_product", "https://amazon.com/dp/B08N5WRWNW") -> "{"title": "Product Name", ...}" web_data_feed("linkedin_person_profile", "https://linkedin.com/in/johndoe") -> "{"name": "John Doe", ...}" web_data_feed( "facebook_company_reviews", "https://facebook.com/company", num_of_reviews=50 ) -> "[{"review": "...", ...}]"
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-03-06 | A+ | 96 | - | v1 |