SCRAPR - The data layer for the agentic web
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SCRAPR is a new approach to web data extraction.
Instead of relying on fragile DOM selectors or heavy browser automation, SCRAPR looks at how modern websites actually load their data and extracts structured responses directly from those sources.
The goal is to make web data pipelines faster, more reliable, and easier to maintain.
Right now SCRAPR is in early MVP and we’re looking for developers, data teams, and AI builders who need clean structured data from websites.
Replies
Smart approach intercepting the underlying API calls instead of fighting the DOM. I've built data pipelines that relied on traditional scraping and the maintenance burden of broken selectors is brutal. Curious -- do you have plans for a schema definition layer where users can map the intercepted responses to a consistent output format? That would make it really useful for feeding structured data into AI workflows.
SCRAPR
Copus
Really smart approach to web scraping. Focusing on where data actually comes from rather than relying on DOM selectors is a much more resilient strategy. Most scraping tools break the moment a site updates its frontend, so anchoring to underlying API calls makes a lot of sense.
Curious about how you handle rate limiting and sites that aggressively block automated access. Either way, congrats on the launch!
SCRAPR
Great implementation! Is the live demo on the website operable? I can't seem to enter text into the fields. Early access requested!
SCRAPR
@joel_farthing Thanks, really appreciate that!
The demo on the site is more of a preview right now, so the input fields aren’t fully interactive yet. I’m working on making a proper live demo soon.
Glad you requested early access — I’ll make sure you get access as we roll out the next version!
Cue
Intercepting network calls instead of rendering pages is a smart approach. Way less fragile than the usual scraping setups. What kinds of sites have been trickiest to support so far?
SCRAPR
@dparrelli Thanks, appreciate that!
Some of the trickier ones tend to be sites that generate requests dynamically or rely heavily on session-based flows, since those can behave differently depending on how the page loads.
But overall most modern sites still rely on some form of underlying data requests.
rtrvr.ai
Wait also @gabe how is this even allowed as per Product Hunt launch rules, this is just a vercel app website with a waitlist?
I thought the product hunt rules were that no waitlists.
SCRAPR
The network-call interception approach is genius. Most scrapers fight against the rendered HTML which is a losing battle - sites redesign constantly and JS-rendered content is a nightmare.
Going upstream to the actual data source (API calls) means you're getting the same clean data the site itself uses. Much more stable.
How do you handle authentication-required data? Like scraping my own logged-in dashboards to aggregate data from various services I use?
This is such a smart pivot from the usual DOM-parsing headaches! As a dev who's spent way too many hours fixing scrapers because of a tiny CSS change, focusing on the data responses directly sounds like a lifesaver. How do you handle sites with heavy anti-bot protections or obfuscated API endpoints?
The "data layer for the agentic web" framing is interesting - curious how you're handling anti-bot countermeasures that vary by target site. Are you routing through rotating proxies or using something more sophisticated on the infrastructure side? Asking because this seems like it gets complicated fast at scale.
This looks sick, just signed up for early access! How do you deal with users who want to scrape websites when it's against their TOS? Would love to try this for my use case (auction websites).
Looks awesome. Signed up for the waitlist and added you on LinkedIn@vemulasukrit Any ETA on when this beta will go live? Would love to test this out!