AI · GitHub repo
Firecrawl Agent
Autonomous web data extraction API driven by prompts without needing explicit URLs.
Firecrawl Agent is an API endpoint that searches, navigates, and scrapes websites autonomously based on a natural language prompt. Instead of manually providing target URLs or writing crawling logic, developers supply a prompt and a schema to get structured JSON back. It handles dynamic pages, pagination, and multi-source research tasks automatically.
What it's for
- Extract founder and executive information for lead generation
- Gather pricing and listing details across e-commerce catalogs
- Curate custom datasets from research papers, real estate, or directory sites
- Automate market research lookups across multiple public company profiles
Features
- URL-optional scraping driven purely by natural language prompts
- Type-safe structured JSON output via Pydantic or Zod schemas
- Autonomous search and navigation across complex, dynamic JavaScript sites
- SDK and integration support across Python, Node.js, cURL, and CLI
- Configurable reasoning effort and credit limits via maxCredits
Pricing
Freemium. 5 free daily runs; dynamic credit-based usage depending on query complexity
Details
- Type
- GitHub repo
- Category
- AI
- Topic
- Web Scraping
- Open source
- No
- Platforms
- API, Code library, Command line, Web
- For
- Developers and AI engineers building automated web data pipelines and agent workflows.
- Alternative to
- Tavily, Apify, Browserbase
- Tags
- web scraping, ai agent, data extraction, firecrawl, api, structured data
Why it was saved
- @ericciarla: Shows how to build an agentic crawl pipeline: Google search for a company, R1 filters URLs, /extract pulls structured data, R1 deduplicates and consolidates it into JSON.
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Updated