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 wh000wh000 · MCP Server · ★ 129
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-jev-live safe to install? View the security audit →
Awesome Jev Live The evidence-graded Jev index that rebuilds itself every two hours. English · 简体中文 · 繁體中文 · 日本語 · 한국어 · Español · Français · Deutsch · Português (Brasil) · Русский · Italiano · العربية · हिन्दी · Türkçe · Tiếng Việt · ไทย · Bahasa Indonesia · Polski · Nederlands · Українська [!NOTE] Live index · Last s
| Stars | 129 |
| Forks | 6 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 52.1787987652168/100 |
| Open Issues | 5 |
| Last Updated | 2026-10-03 |
| Created | 2026-09-18 |
| Platforms | mcp, python |
| Est. Tokens | ~25k |
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awesome-jev-live is Awesome Jev — evidence-graded index of TypeSafe System One: SDKs, MCP tools, agents, apps and open models. 20 languages, rebuilt every 2 hours.. It is categorized as a MCP Server with 129 GitHub stars.
awesome-jev-live is primarily written in Python. It covers topics such as ai-agents, artificial-intelligence, awesome.
You can find installation instructions and usage details in the awesome-jev-live GitHub repository at github.com/wh000wh000/awesome-jev-live. The project has 129 stars and 6 forks, indicating an active community.
The top alternatives to awesome-jev-live on Agent Skills Hub include awesome-jev, awesome-typesafe-jev, awesome-jev-gallery. 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: