Firecrawl vs Apify vs Browserless — which is best for agents?

For AI agents specifically, Firecrawl wins on out-of-the-box LLM-ready markdown, Apify wins on scale and pre-built scrapers ("Actors"), and Browserless wins when you need real browser execution — but all three are designed primarily for traditional scraping pipelines, not agent runtimes. Firecrawl pricing starts at $19/mo (Hobby, 3,000 pages) and scales to $99/mo (Standard, 100k pages); it returns clean markdown by default which suits LLM context budgets. Apify is actor-based — you pick or build a scraper from their marketplace — and pricing is compute-time-based, typically $0.25/hour of actor runtime, more economical at very high volume (>1M pages/mo). Browserless rents headless Chrome instances starting at $50/mo; use it only when you need JS execution, screenshots, or session-based scraping. For agent developers using Claude Desktop, Cursor, or Cline, none of these are MCP-native — you'll write glue code or use a community wrapper. An MCP-first option like AgentFetch is usually simpler for the agent use case; reserve Firecrawl/Apify/Browserless for backend pipelines outside the agent loop.