No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by SerendipityOneInc · MCP Server · ★ 73
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ZooData-Skills safe to install? View the security audit →
English | 中文 ZooData Skills The data infrastructure built for agents. Currently powering Amazon commerce with 200M+ products, 1B+ reviews, and real-time signals. Website • Get API Key • Discord • Quick Start • API Reference What is ZooData? ZooData is the data infrastructure built
| Stars | 73 |
| Forks | 10 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 71.4348387660335/100 |
| Open Issues | 6 |
| Last Updated | 2026-09-17 |
| Created | 2026-03-13 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~17k |
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ZooData-Skills is ZooData Skills - AI Agent skills for e-commerce data intelligence across Amazon, TikTok & beyond, plus open-web extraction. It is categorized as a MCP Server with 73 GitHub stars.
ZooData-Skills is primarily written in Python. It covers topics such as ai-agent, ai-agents, amazon.
You can find installation instructions and usage details in the ZooData-Skills GitHub repository at github.com/SerendipityOneInc/ZooData-Skills. The project has 73 stars and 10 forks, indicating an active community.
ZooData-Skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ZooData-Skills on Agent Skills Hub include PolyMCP, awesome-amazon-ec-skills, alfanous. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: