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ZooData

Data infrastructure layer that converts any URL into structured, agent-ready JSON with built-in e-commerce intelligence.

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Product Overview

What is ZooData?

ZooData is a data layer built specifically for AI agents and developers who need clean, structured data instead of raw HTML or oversized markdown. Rather than forcing agents to parse messy web pages, ZooData converts any URL into agent-ready JSON, cutting LLM token consumption by roughly 75%. Beyond basic extraction, the platform layers on pre-analyzed e-commerce intelligence for Amazon and TikTok, covering competitor tracking, market trends, traffic data, and consumer behavior, all accessible via API, CLI, or MCP server.


Key Features

  • URL-to-JSON Conversion

    Transforms any webpage into clean, structured JSON output, removing the noise of raw HTML and bloated markdown formatting.

  • Token-Efficient Design

    Reduces LLM token usage by approximately 75% compared to feeding agents unstructured page content.

  • Pay-Per-Field Pricing

    Users pay only for the specific data fields they actually use, avoiding extra charges for unnecessary extraction credits.

  • E-commerce Intelligence Layer

    Delivers pre-analyzed insights on competitors, market trends, traffic, and consumer behavior for Amazon and TikTok sellers.

  • Multi-Interface Access

    Supports API, CLI, and MCP server integration, giving developers flexibility in how they connect ZooData to their workflows.

  • Free Starter Tier

    New users receive 1,000 free credits with no credit card required, allowing risk-free testing before committing.


Use Cases

  • AI Agent Data Pipelines : Developers building autonomous agents can feed them structured JSON instead of raw scraped content, improving reliability and reducing costs.
  • E-commerce Competitor Research : Sellers and analysts can monitor competitor pricing, positioning, and performance across Amazon and TikTok in real time.
  • Market Trend Analysis : Product teams can track category-level trends and shifts in consumer demand to guide sourcing and inventory decisions.
  • LLM Cost Optimization : Teams running high-volume scraping or extraction tasks can significantly cut LLM inference costs by pre-structuring input data.
  • Web Data Integration : Engineers can plug ZooData into existing pipelines via API or MCP server to standardize how external web data enters their systems.

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