Web Scraping APIs for AI Agents: Firecrawl vs ScraperAPI vs Apify

Web Scraping APIs for AI Agents: Firecrawl vs ScraperAPI vs Apify Agents need reliable web data extraction. Three platforms dominate: Firecrawl (LLM-native), ScraperAPI (general purpose), and Apify (versatile platform). This comparison uses Rhumb AN Scores — evaluating web scraping APIs specifically for agent-readiness: execution reliability, structured extraction, handling complex JavaScript sites, and failure modes that agents must defend against. The Scores Provider AN Score Execution Access Readiness Flexibility Confidence Firecrawl 7.2 7.8 7.1 7.2 73% ScraperAPI 7.0 6.9 6.8 7.8 71% Apify 7.2 7.4 6.9 7.6 72% Firecrawl: "Built for LLM pipelines" (7.2 / 10) Best for: Agents that need markdown from complex sites with minimal config. LLM-native output format, zero JavaScript handling overhead, designed specifically for agent use. Biggest friction: Markdown extraction can miss structured data (tables, lists) that pure HTML would preserve. LLM-specific design means if you need raw HTML o