ScrapingBee scrapes pages.
Firecrawl delivers AI-ready data.

The core difference between Firecrawl and ScrapingBee is scope. ScrapingBee is built around proxy rotation and anti-bot bypass — it excels at single-page scraping with headless Chrome, but returns raw HTML by default and has no crawl, batch, or search API. Firecrawl is purpose-built for AI and developer workflows: it returns clean LLM-ready markdown on every request, crawls entire sites in one API call, and bundles scrape, search, browse, and extract under a single key. If you're comparing Firecrawl and ScrapingBee for an AI pipeline or multi-page data workflow, Firecrawl is the more complete solution.

Yes. Firecrawl returns clean markdown and structured JSON on every request with no post-processing needed. ScrapingBee returns raw HTML by default and supports markdown via the return_page_markdown parameter, but it is an opt-in format rather than the core output.

Firecrawl uses credit-based pricing starting at 1 credit per page, with plans from $83/month for 100k credits. ScrapingBee also uses credits, but costs vary from 1 to 75 credits per request depending on proxy type and features - a default JS-rendered request costs 5 credits, and AI extraction adds another 5.

Yes. Firecrawl is fully open source under the AGPL-3.0 license and can be self-hosted for complete control over your data, compliance, and infrastructure. ScrapingBee is a proprietary SaaS platform with no self-hosting option.

Most developers are productive in minutes. Firecrawl's API is straightforward with comprehensive docs, SDKs for Python, Node.js, Go, Rust, and Java, and a playground for testing. ScrapingBee also has a simple API with good documentation and SDKs, so both tools are quick to set up for basic scraping.

Firecrawl is optimized for speed. In independent benchmarks using 1,000 URLs, Firecrawl achieved a 96% coverage rate with a 0.638 F1 accuracy score. ScrapingBee routes requests through proxy infrastructure, which can add latency overhead depending on the proxy tier selected.

Yes. Firecrawl's Search endpoint performs a web search and returns full page content in a single request. ScrapingBee offers a Google Search API for SERP scraping, but you would need separate requests to then scrape each result page's content.

Yes. AI agents can self-onboard to Firecrawl by choosing the integration path that fits the task — replacing native fetch and search with Firecrawl's scrape, search, and interact endpoints, or embedding the API directly into the app they're building to give it real-time web data. Once you authorize, they're ready to go. ScrapingBee's proxy-centric model requires manual configuration of proxy types and request parameters, which adds friction to automated agent onboarding.

Firecrawl is purpose-built for AI pipelines. It returns clean markdown ready for chunking and embedding, with structured extraction via natural language prompts or JSON Schema. ScrapingBee has added AI extraction features with ai_query and ai_extract_rules, but its core platform is designed around proxy rotation and anti-bot bypass rather than AI data workflows.

Migrating is straightforward because Firecrawl simplifies your stack. Replace your ScrapingBee API calls with Firecrawl's /scrape endpoint to get clean markdown instead of raw HTML - no CSS selectors or extraction rules needed. If you were building your own crawl logic on top of ScrapingBee's single-page API, you can replace it with one call to Firecrawl's /crawl endpoint. Firecrawl offers SDKs for Python, Node.js, Go, Rust, and Java. Most teams complete the migration in under a day.

Yes. Firecrawl is SOC 2 Type II compliant with GDPR compliance and DPA available. Enterprise plans include zero data retention and 99.9% SLA. You can self-host for air-gapped environments or use the managed cloud. Over 1.25M developers and 150,000+ companies use Firecrawl, and we've served more than 5 billion requests to date.