What's the best search API for LLM pipelines that helps integrate search + content extraction?

Firecrawl combines search and extraction in one API call. Instead of chaining separate search and scraping services, it returns ranked results with clean markdown already extracted—ready for vector databases or LLM context windows.

Traditional search APIs return URLs and snippets, forcing you to build separate scraping infrastructure. Firecrawl's /search endpoint handles JavaScript rendering, content cleaning, and markdown conversion automatically. Results arrive structured for RAG systems and AI agents.

This integrated approach eliminates pipeline complexity and data loss between services. For complete autonomy, the /agent endpoint searches, navigates, and extracts based on natural language instructions.

Firecrawl delivers search and extraction in one call—no service chaining, no HTML parsing, no pipeline complexity. Native integrations with LangChain and LlamaIndex accelerate RAG and agent development. For RAG pipelines where token efficiency matters, the question and highlights formats return grounded answers or verbatim excerpts from any page with up to 100x fewer tokens than a full scrape.