Scrape.do gives you raw HTML.
Firecrawl gives you AI-ready data.

The core difference between Firecrawl and Scrape.do is scope. Scrape.do is built as a proxy-based scraping API — it handles anti-bot bypass and JavaScript rendering, but returns raw HTML by default and has no crawl, search, or AI extraction capabilities. 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. When you compare Firecrawl and Scrape.do for an AI pipeline or multi-page data workflow, Firecrawl is the more complete solution with no extra parsing layer required.

Yes. Firecrawl returns clean markdown and structured JSON out of the box with no post-processing. Scrape.do returns raw HTML by default. You can get markdown via their output=md parameter, but there is no built-in LLM-powered extraction or schema-based JSON output.

Firecrawl uses credit-based pricing starting at 1 credit per page, with plans from $16/month for 3,000 credits. Scrape.do starts at $29/month for 250,000 credits, but JS rendering costs 5x and residential proxies cost 10x, so effective costs depend heavily on your use case.

Firecrawl goes further. One API call crawls thousands of pages with automatic sitemap discovery, depth control, and regex filtering. Scrape.do has no crawl endpoint. You would need to build your own link-following logic and manage URL queues yourself.

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. Scrape.do is proprietary with no self-hosting option.

Yes. Firecrawl's agent endpoint lets you describe what data you need in plain language without specifying URLs. The agent autonomously searches, navigates, and extracts structured data. Scrape.do does not offer any agent or autonomous research capability.

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. Once you authorize, they're ready to go. Scrape.do's proxy-centric model requires agents to configure proxy types, JS rendering flags, and output format parameters per request — adding meaningful friction to automated onboarding.

Most developers are productive in minutes. Firecrawl offers official SDKs for Python, Node.js, and Java, plus integrations with LangChain, LlamaIndex, and an MCP server for AI tools. Scrape.do provides HTTP API code samples but no official SDK packages or AI framework integrations.

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. Scrape.do can output markdown via a parameter, but you would need to handle structured extraction, schema mapping, and pipeline integration yourself.

Replace your Scrape.do API calls with Firecrawl's /scrape endpoint. You will get clean markdown instead of raw HTML, eliminating your parsing layer. Firecrawl's SDKs make the swap a few lines of code. If you built custom crawling logic on top of Scrape.do, Firecrawl's /crawl endpoint replaces all of it with a single call.

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 500,000 developers and 80,000+ companies use Firecrawl.