by zymazza · MCP Server · ★ 152
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 152 |
| Forks | 19 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 64/100 |
| Open Issues | 3 |
| Last Updated | 2026-07-24 |
| Created | 2026-02-27 |
| Platforms | mcp, python |
| Est. Tokens | ~21k |
Mazzap v2 — a georeferenced 3D digital-twin engine https://github.com/user-attachments/assets/deb9e860-abf8-4e34-ab9b-88b3c7a2643f Mazzap v2 turns a patch of real ground into a standalone, fully georeferenced 3D digital twin you can open in a browser, click to read true GPS coordinates, drape your own map layers onto the terrain, and ask questions about in natural language.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: