What is SCRAPR?

SCRAPR is a web data extraction API that captures structured JSON directly from a website's internal network requests — without rendering a browser or using fragile DOM selectors. By replaying the exact HTTP/XHR calls a site makes to load its own data, SCRAPR delivers clean, AI-ready output in under 200 milliseconds. It's currently in early MVP with over 835 engineers on the waitlist.

Who it's for

• AI engineers building autonomous agents that need reliable, live web data without the overhead of headless browsers
• Data teams running RAG pipelines or knowledge bases that require continuous ingestion of structured content from multiple websites
• ML practitioners generating labelled training datasets from real-world web sources, where HTML noise would otherwise corrupt model inputs

Key features

Network-level extraction

SCRAPR intercepts and replays the same HTTP/XHR calls a website uses to populate its own interface. This eliminates browser spin-up time and render delays, achieving average extraction speeds of 89ms — 10 to 100 times faster than Puppeteer-based solutions.

Auto schema detection

Types, keys, and data structure are inferred automatically from each API response. Strings, arrays, and numbers arrive correctly typed in the output JSON, ready for direct use in LLM contexts, vector stores, or agent memory.

Zero-selector maintenance

Because SCRAPR targets internal data APIs rather than DOM elements, extraction pipelines don't break when a site redesigns its CSS. The underlying data endpoints change far less often, reducing ongoing maintenance to near zero.

Global infrastructure

Over 437 active nodes across 190+ countries provide worldwide coverage with a 99.9% success rate. The service supports batch extraction, webhook notifications, and async job processing for large-scale data operations.

What stands out

"The extraction layer that doesn't break."

SCRAPR rethinks web scraping by treating each website as its own API. Instead of simulating a user browsing a page, it captures the structured data the site already sends to itself. This approach yields faster, more reliable results and eliminates the constant selector-updating cycle that plagues traditional scrapers. The output is clean JSON — no HTML parsing, no regex cleanup, just typed data ready for AI pipelines.

Worth checking out if…

You're building AI agents, RAG systems, or data pipelines that depend on fresh, structured web content. If you've been frustrated by slow headless browsers, brittle CSS selectors, or the maintenance burden of traditional scraping tools, SCRAPR offers a fundamentally different approach. It's especially relevant for teams that need to extract data at scale — batch endpoints and webhook support are already in alpha, and the REST API is stable at v1.