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 rohitg00 · MCP Server · ★ 960
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is kubectl-mcp-server safe to install? View the security audit →
kubectl-mcp-server Control your entire Kubernetes infrastructure through natural language conversations with AI. Talk to your clusters like you talk to a DevOps expert. Debug crashed pods, optimize costs, deploy applications, audit security, manage Helm charts, and visualize dashboards—all through natural language. <a href="https://www.npmjs.com/package/kubectl-mc
| Stars | 960 |
| Forks | 184 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.7580437928526/100 |
| Open Issues | 7 |
| Last Updated | 2026-04-08 |
| Created | 2025-03-23 |
| Platforms | k8s, mcp, python |
| Est. Tokens | ~6510k |
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kubectl-mcp-server is Published in CNCF Landscape: A MCP server for Kubernetes.. It is categorized as a MCP Server with 960 GitHub stars.
kubectl-mcp-server is primarily written in Python. It covers topics such as ai, deployment, devops.
You can find installation instructions and usage details in the kubectl-mcp-server GitHub repository at github.com/rohitg00/kubectl-mcp-server. The project has 960 stars and 184 forks, indicating an active community.
kubectl-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to kubectl-mcp-server on Agent Skills Hub include mcp-for-argocd, mcp-context-forge, radar. 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: