Search the web and get full content from results

This endpoint goes beyond a simple search API by returning the full markdown content of the top results. It's designed to give AI agents the context they need to answer questions or perform research without making separate requests for each URL.

Business outcome: Enables AI agents to perform deep research and answer questions with up-to-date web data in a single API call.

Get LLM-ready data from any website

Firecrawl's core scraping feature converts any webpage into clean markdown, JSON, or a screenshot. It handles JavaScript rendering and smart waiting, meaning it can reliably extract content from modern, dynamic sites that often break traditional scrapers.

Business outcome: Provides a reliable, token-efficient way to ingest web content into AI models, reducing preprocessing overhead.

Crawl entire websites for comprehensive data collection

The crawl endpoint allows you to systematically explore a domain and extract data from multiple pages. This is essential for building knowledge bases, monitoring competitor sites, or collecting large datasets for analysis.

Business outcome: Automates large-scale data collection from websites, saving countless hours of manual work and enabling comprehensive analysis.

Map website structures to understand data landscapes

The map endpoint provides a bird's-eye view of a website's structure by listing its URLs. This is useful for planning a crawl, understanding a site's architecture, or quickly discovering all pages related to a specific topic.

Business outcome: Helps teams quickly understand and plan web data collection, making projects more efficient from the start.

Interact with pages using AI prompts or code

This newer feature allows you to go beyond simple scraping by performing actions on a page, such as clicking, scrolling, or typing. This is critical for extracting data from behind login forms, navigating complex web apps, or testing user flows.

Business outcome: Enables automation of complex web interactions, unlocking data from dynamic and gated web applications.

Transparent and collaborative development

With a public GitHub repository and over 171.8K stars, Firecrawl's core is open source. This provides a level of transparency and trust that is rare in the AI infrastructure space, allowing businesses to inspect the code and contribute to its development.

Business outcome: Reduces vendor lock-in and provides confidence in the tool's security and reliability through community scrutiny.

• Reliability on modern webIndustry-leading reliability that covers 96% of the web, including JS-heavy pages, where many other tools fail.
• Token-efficient outputDelivers clean markdown with 93% fewer input tokens, significantly reducing LLM processing costs.
• Developer-first experienceOffers a straightforward API, SDKs for Python and Node.js, and a CLI, making integration fast and simple.
• Open-source coreThe open-source nature builds trust and allows for community contributions and self-hosting options.

• Credit-based pricingCosts can scale quickly for large-scale crawling or frequent search operations, requiring careful budget management.
• No pay-per-use planThere is no pay-as-you-go option; users must purchase a monthly subscription even for occasional use.
• Credits don't roll overOn self-serve plans, unused credits expire at the end of the month, which may not suit variable workloads.
• Professional RealityThe most important thing to know is that Firecrawl is an infrastructure tool for developers, not a no-code solution; its value is only realized when integrated into a technical workflow.

RAG Pipeline Development

For teams building retrieval-augmented generation (RAG) systems, Firecrawl's scrape and crawl endpoints provide a reliable way to ingest and structure data from a wide range of sources, ensuring the AI has access to current and relevant information.

AI Agent Tooling

Firecrawl is designed to be an agent-ready tool. Its search and scrape capabilities can be integrated directly into AI agents, allowing them to browse the web, gather information, and complete tasks autonomously.

Deep Research

Businesses conducting deep research can use Firecrawl to automatically gather and synthesize information from academic papers, news articles, and industry reports, turning a manual research process into an automated one.

Competitive Intelligence

By crawling competitor websites and monitoring pricing or product pages, teams can build a real-time competitive intelligence feed to inform strategic decisions.

Sign up for a free account at firecrawl.dev to get your API key.

Install the official Python SDK (pip install firecrawl-py) or Node.js SDK.

Use the API key to make your first scrape request on a simple URL to understand the markdown output.

Explore the search and crawl endpoints to test them on your specific use case, such as a competitor's website.