ZooData

Great launch! The token math is the part that really matters, at least for agents. Paying to filter boilerplate out of 'clean' markdown is a tax you don't price in until the bill shows up! Wondering - when a site quietly ships a layout change or runs an A/B test, does that learned template keep mapping to the old fields and hand back a confidently wrong value?

curious how this holds up against anti-bot layers - a lot of the messiest sites to scrape aren't messy because of markup, they're messy because they actively try to block automated requests. does the per-field pricing still apply if a site just serves you a captcha wall instead of html, or is that a separate failure case

Skipping extra extraction credits and just paying for what you use is how all these tools should work. The included CLI makes it very easy to test the data formatting locally.

Any tool that helps agents work with structured data instead of messy web scrapes is a win. The included CLI is a nice touch for those of us who prefer working from the terminal.

Paying only for the fields used makes a lot of sense for data extraction.

Really glad to see an MCP server included from day one. It shows a deep understanding of current developer workflows and makes integrating this JSON extraction much more appealing.

Getting clean JSON straight from a URL is literally a lifesaver for agent workflows. Skipping the raw HTML mess will save so much time and token costs.

The fact that it comes with a CLI and API ready to go is super helpful for developers trying to integrate this quickly.

is this restricted to English? I've tried two .ro websites and got nothing back.

Hi PH 👋,I'm Ning from ZooData. Quick context on why we built this.If you've built anything with agents, you know the data problem. You scrape a page — with browser-use, Playwright, whatever — and what comes back is raw HTML or "clean" markdown. Either way it's stuffed with nav bars, footers, ads, and boilerplate. For a human reading it, fine. For an LLM, you're burning thousands of tokens on stuff the model has to filter out before it can do anything useful. At scale that's real money, and most of it is waste.Markdown is the usual fix. But markdown was built for humans to read, not for an agent that has to act on the data. Different reader, different format — an agent doesn't need prose, it needs structure. ZooData does the extraction step right:Any URL → structured JSON. No schema to define, no per-site parsers, no selector glue to maintain.~75% fewer tokens than raw markdown on the same page — roughly 1/5 the cost of other extractors. And you only pay for the fields you actually use; the extraction itself doesn't burn credits.API, CLI, and MCP server, so it drops into your agent stack without rewriting anything.Pre-analyzed e-commerce platform intelligence — competitor, market, traffic, and consumer signals your agent can query directly, instead of scraping and stitching it together itself. More platforms coming.We believe the next bottleneck for AI agents won't be how smart the models get — it will be the quality of the data they rely on.As AI-generated content floods the web, agents need data that's clean, structured, and verifiable to make reliable decisions. That's the layer we're building, and it compounds: every page we process makes the next request cheaper, faster, and more trustworthy.ZooData is the foundation the rest of it runs on — we launched ZooClaw (agents for individuals) here not long ago, and ZooWork (the enterprise version) is coming soon.1,000 free credits, no card. Just tell your agent:npx skills add SerendipityOneInc/ZooData-Skillsand you're off.Would love your feedback. And I'm curious — what's the messiest site you've ever had to scrape? 🙏