Structured JSON responses
Endpoints return clean JSON structured for LLM consumption, with pre-processed fields that reduce parsing overhead.
ZooData
ZooData is an agent-native commerce intelligence API for structured product, competitor, market, and historical data with clean JSON and realtime signals.
Agent-native commerce data for AI workflows
ZooData is an agent-native commerce intelligence API for teams building AI workflows around product research, competitor monitoring, market analysis, and related e-commerce tasks. The product is positioned as a data layer for agents rather than a human dashboard or a generic scraping service.
Its core output is structured, decision-ready data: clean JSON responses, pre-processed insights, and endpoints for live, historical, and category-level commerce signals. The site emphasizes that one integration can replace multiple separate data sources for agents that need continuous access to product and market information.
The platform is designed for workflows that need both breadth and freshness, including product search across large catalogues, competitor lookup by brand or ASIN, realtime pricing and inventory checks, and historical trend analysis. ZooData also provides a web console, OpenAPI documentation, and framework integrations so teams can use it directly or inside existing agent stacks.
Pricing is presented as credit-based and usage-driven, with prepaid API credit packages and a separate web plan. The pricing page also notes a free Basic web tier for exploration and a Pro plan for power users.
Core features
Commerce intelligence endpoints
The API includes product search, competitor lookup, market analysis, realtime product data, and historical trend data.
Large product coverage
The site states that the platform tracks 500M+ products across Amazon and TikTok Shop, with 40+ filters for product search.
Historical and realtime data
Historical endpoints provide more than two years of BSR, price, sales, and rating history for trend analysis.
Agent-oriented integration
Inputs and outputs are built for agent tool-calling, including OpenAPI 3.0 support and import paths for LangChain, CrewAI, AutoGen, and Claude MCP.
Specialized workflows and skills
The platform includes image-to-attributes product tagging and pre-built skills for workflows such as market validation, product selection, competitor analysis, pricing strategy, and daily operations.
Practical use cases
Autonomous product research
Use ZooData to scan large product sets for opportunities using filters, preset modes, and market signals. The source describes workflows that let an agent review far more products per day than a human researcher could manually.
Competitor monitoring
Monitor competitors for price changes, new listings, and review shifts using competitor lookup plus realtime product queries. The source emphasizes continuous monitoring and second-level alerts for market changes.
Dynamic pricing support
Combine market analysis, realtime product data, and competitor prices to support pricing decisions. The product is positioned as the data layer feeding a pricing agent rather than a standalone pricing app.
Market trend monitoring
Track category trends, BSR movement, and emerging signals on a schedule to identify changes as they happen. The source frames this as continuous market radar rather than static reporting.
Listing automation
Build end-to-end listing pipelines that move from opportunity discovery to validation and listing generation. The site describes a workflow that can connect discovery, real-time checks, and publishing in one agent flow.
Pros and Cons
Pros
- Returns clean, structured JSON that is ready for LLM and agent consumption.
- Combines live product data with more than two years of historical history for trend analysis.
- Covers several commerce workflows in one API, including search, competitor lookup, market analysis, and realtime product queries.
- Supports agent frameworks and tool-calling through OpenAPI 3.0 and documented import paths.
- Offers usage-based credit pricing rather than seat-based SaaS pricing for API plans.
Cons
- The public evidence is partial, so some implementation details such as exact SDK coverage, data sources, and full output schemas are not documented here.
- The product is specialized for commerce and e-commerce intelligence, so it is not presented as a general-purpose data platform.
FAQ
What is ZooData used for?
ZooData is used by AI agents that need structured commerce data for research, competitor tracking, market analysis, or listing workflows. The API returns clean JSON and supports agent-oriented endpoints such as product search, competitor lookup, market analysis, realtime product data, and historical data.
How do you get started with the API?
The source shows a straightforward setup flow: get an API key, make a POST request to an endpoint, and receive structured JSON. The site also mentions an OpenAPI 3.0 spec and import paths for frameworks such as LangChain, CrewAI, AutoGen, and Claude MCP.
Can it be used with other AI tools or frameworks?
ZooData supports both automated agent workflows and a web console for manual research. The site also points to pre-built skills and OpenAPI-based integration for AI frameworks, so it can fit either direct API use or a broader agent stack.
What kind of data does it return?
The API is focused on commerce intelligence rather than generic web scraping. Documented outputs include product search, competitor intelligence, market analysis, realtime product data, historical trends, and product tags.
Is there a free option?
The pricing page shows both prepaid credit packages and a web plan with a free Basic tier and a paid Pro tier. It also states that credits can be bought when needed and that there are no subscriptions or seat limits for API plans.
Quick Facts
- Category
- Commerce intelligence API
- Primary users
- AI agents and teams building agent workflows
- Output format
- Clean JSON
- API style
- OpenAPI 3.0 / POST endpoints
- Pricing model
- Credit-based API pricing; separate web plans
- Website domain
- zoodata.ai
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