ZooData
The data layer for AI agents
833 followers
The data layer for AI agents
833 followers
ZooData turns any URL into agent-ready JSON, so AI agents can work with structured data instead of raw HTML or bloated markdown. Use ~75% fewer LLM tokens, pay only for the fields you use, and skip extra extraction credits.Beyond extraction, ZooData gives agents pre-analyzed e-commerce intelligence — competitor, market, traffic, and consumer insights — live for Amazon and TikTok. API, CLI, and MCP server included. Start with 1,000 free credits, no card required.
@Kyle Dong that three-lane breakdown (retryable / don't-retry / content-ok-but-degraded) is actually clearer than most APIs give you even without the granular attribution. makes sense you'd keep the fine-grained block signals internal rather than publish a map of exactly what trips detection. appreciate the detailed answer
ZooData
@omri_ben_shoham1 Thanks! The three lanes come from a simple inversion: instead of asking "how much error detail can we expose," we asked "where does your agent's control flow actually branch" — it branches three ways, so the API only needs to be clear about three things. Every extra lane would just be a branch you write and never take. If you ever hit a case where three lanes aren't enough, come back and challenge that claim
I can see that for e-commerce you already provide some more custom workflows, I'd love to see the same for general startup pages - like being able to get a startup's pricing or products overview in JSON
ZooData
@wojtekszkutnik Your instinct about the direction is exactly right — it's how we think about the product ourselves: a general extraction layer underneath, vertical workflows growing on top. E-commerce is just the first vertical we grew, not the only shape it takes.
What works today: point the general extraction at those pages. Page types are auto-detected — pricing pages with tiered plan cards are naturally list-shaped (each plan with a name, price, description), and company home/about pages tend to land as entity-type, coming back as structured facts plus the page's outgoing links. No promise that every startup page parses perfectly — but the general layer will likely take you further than you expect. Worth a round with a few real targets.
After that round, whatever the outcome, send us the URLs plus the fields you wished you'd gotten (support@zoodata.ai) — that's literally how verticals get built here: the e-commerce depth endpoints started with users throwing real pages at the general layer. A startup pricing page is a well-bounded page class, and your ask is noted.
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.
ZooData
@glsm11117961978 Thanks! One design detail worth sharing: our MCP tools and REST API are generated from the same codebase — every endpoint's schema, description, and validation share a single source, so the MCP tools never drift out of sync with the API. The server side is also fully stateless, so any MCP client stays reliable at any scale. If anything feels rough in your integration, tell us — we'll fix it!
ZooData
@grrigore Thanks for flagging — it's not English-only by design; the open-web extraction is language-agnostic. One thing worth knowing: when we encounter a brand-new page type, the first extraction takes extra time (the system first works out the structure for that type of page — after that, similar pages are fast). Please give it another try in a bit; if you still get nothing back, send us the two URLs (here or at support@zoodata.ai) and we'll confirm what's going on — and report back.
@kyle_dong Yes, it works now. It might be helpful to share that explanation with the user as well. Is there a way to automatically scrape "outgoing_links"?
ZooData
@grrigore Great question! Two cases:
① Entity-style pages — outgoing links are already included by default. If the page is about one specific named thing (think a HuggingFace model page, an IMDB movie page, a Goodreads book page — one subject, structured facts around it), the extracted JSON already carries the page's outgoing links, no extra parameters needed.
② Other page types — a dedicated endpoint exists, just not public yet. We've built a dedicated outgoing-links capability internally but haven't opened it up. So: try the default output on your actual pages first. If it covers you, great; if it doesn't, tell us your page types and use case — your scenario is exactly the push we need to release it. Find us here or at support@zoodata.ai.
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.
ZooData
@irmakb5o5 Thanks! Everyone counts the token bill, but the "time" part you mentioned is the bigger one — every team that parses HTML themselves ends up babysitting a pile of selectors and cleanup scripts that shatter on every redesign. Outsourcing the "URL → fields" step saves more than tokens; it retires an entire maintenance pipeline. That's exactly the part we want to carry for you. 🙌
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.
ZooData
@elifeakekep6oh Thanks! That's a deliberate choice: structured JSON is the default output, not a paid add-on. The way we see it, structure is the product — charging extra for clean fields would be billing twice for the core value. One call, one price, structure included.
ZooData
@arokamal_sethy Nope — no token billing on our side; extraction is flat credits per call. Tokens only happen when your own LLM reads the result — and structured JSON exists precisely to keep that part as small as possible.