Exa vs Tavily vs Serper vs Brave Search for AI Agents — AN Score Comparison

Search is the most fundamental thing an agent does. Before it writes, plans, acts, or decides — it looks something up. You'd expect this to be a solved problem. It mostly is. But "mostly" is where agents fail. We scored five search APIs on Rhumb's AN Score framework: 20 dimensions covering execution reliability, error quality, auth predictability, and access readiness. The spread is narrower than CRMs or databases — search APIs are simpler primitives — but the differences compound when your agent runs search loops overnight. The Scores API AN Score Tier Key Strength Exa 8.7 L4 Native Neural retrieval, structured output, agent-first design Tavily 8.6 L4 Native Purpose-built for agents, clean response schema Serper 8.0 L4 Native Google results, developer-friendly, predictable errors Brave Search 7.1 L3 Ready Independent index, privacy-first, solid but generic Perplexity 6.8 L3 Ready Returns synthesis, not raw results — changes the contract These aren't bad scores. Search APIs score highe