Web scraping vs. search API for LLM apps

Scraping is best suited to applications that begin with known URLs and require deterministic access to exact fields, fixed-page monitoring, full-site crawls, logged-in workflows, or interactive browser behavior, while search APIs are more effective for question-first applications that need to discover and rank relevant sources before retrieving content. Tests across documentation, news, Wikipedia, a JavaScript-rendered directory, and a PDF found that raw HTML averaged roughly 47,600 tokens per page, compared with 8,200 for extracted full content and 1,600 for objective-specific excerpts, making targeted extraction substantially cheaper for frontier-model prompts despite low per-request fetch costs. Results also showed important limitations: JavaScript pages may require rendering and scrolling, publisher restrictions can yield partial or unavailable content, and extraction services do not bypass CAPTCHAs or anti-bot controls. The recommended hybrid workflow is to search for ranked sources and then extract focused excerpts from the strongest URLs, while routing inaccessible, highly interactive, or site-specific cases to a scraper. Legal, robots.txt, platform terms, and evolving crawler restrictions remain relevant regardless of whether crawling is operated directly or by an API provider.

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