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 zw008 · MCP Server · ★ 63
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is VMware-AIops safe to install? View the security audit →
VMware AIops Author: Wei Zhou, VMware by Broadcom — wei-wz.zhou@broadcom.com This is a community-driven project by a VMware engineer, not an official VMware product. For official VMware developer tools see developer.broadcom.com. English | 中文 AI-powered VMware vCenter/ESXi VM lifecycle and deployment tool — 31 tools across 6 categories. Companion skills handle everything else: Need read-only monitoring only? Use VMware-Monitor — zero destructive code in the codebase. [![License:
| Stars | 63 |
| Forks | 9 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.7666175276244/100 |
| Last Updated | 2026-07-25 |
| Created | 2026-02-25 |
| Platforms | claude-code, cli, codex, gemini, mcp, python |
| Est. Tokens | ~22k |
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VMware-AIops is VMware vCenter/ESXi AI-powered monitoring and operations. Two skills: vmware-monitor (read-only, safe) and vmware-aiops (full operations) | Claude Code Skill. It is categorized as a MCP Server with 63 GitHub stars.
VMware-AIops is primarily written in Python. It covers topics such as agent-skills, ai-skill, aiops.
You can find installation instructions and usage details in the VMware-AIops GitHub repository at github.com/zw008/VMware-AIops. The project has 63 stars and 9 forks, indicating an active community.
VMware-AIops is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to VMware-AIops on Agent Skills Hub include VMware-AIops, agent-skills, code-abyss. 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: