ZooData, a new "data layer for AI agents," launched on July 18, 2026 and immediately topped Product Hunt as the day's number one product. Instead of handing an agent raw HTML or scraped markdown, ZooData turns a URL into clean, structured JSON that an agent can act on directly, and ships pre-processed Amazon commerce data covering more than 200 million products and over a billion reviews.

Try It in Under 30 Minutes

If you build agents in Claude Code or Cursor, ZooData plugs in through a REST API, a CLI, or an MCP server. The fastest path is the open-source Skills package, which is MIT licensed: run npx skills add SerendipityOneInc/ZooData-Skills, set your ZOODATA_API_KEY, and your agent gets 11 ready-made skills for market research, competitor analysis, pricing, and review mining. It is the same wiring pattern as any other tool server, so if you have already connected an MCP server to Claude or ChatGPT, you can have this running against live data in a single session.

Why It Matters for Creators

Builders wiring data into agents usually burn tokens dumping full pages into context. ZooData claims roughly 75 percent fewer tokens than markdown extraction by returning only the fields an agent asks for, billed per field. Because it exposes a Model Context Protocol server, it drops into the same orchestration layer as your other tools rather than forcing a separate scraping pipeline. It sits in the same emerging category as agent-memory tools like AgentPrizm, but focused on external web and commerce data instead of an agent's own recall.

Key Details

Access: REST API, CLI, and MCP server, plus 11 open-source agent skills.

Data: More than 200 million indexed products, two-plus years of history, and over a billion reviews across 11 endpoints.

Pricing: Freemium, one credit per API call, with 1,000 free credits and no card required from the API keys page.

What to Do Next

Start with a narrow job: point one ZooData skill at a product category and have your agent summarize fast-moving listings or extract review sentiment, then compare the token cost against your current scraping step. If the field-level billing holds up in practice, promote it from a weekend experiment to a standing tool in your agent stack.