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 OptimNow · MCP Server · ★ 50
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cloud-finops-skills safe to install? View the security audit →
cloud-finops-skills Built by OptimNow. Covers cloud financial management across AWS, Azure, GCP, AI inference costs, GenAI capacity planning, SaaS asset management, and tagging governance - grounded in enterprise delivery experience. Install in 5 seconds [Download the latest release zip](https://github.com/OptimNow/cloud-finops-skills/releases/latest
| Stars | 50 |
| Forks | 16 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 60.8732674638655/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-09 |
| Created | 2026-02-25 |
| Platforms | aws, claude-code, k8s, mcp, python |
| Est. Tokens | ~21k |
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cloud-finops-skills is Cloud FinOps Skill & MCP by OptimNow. FinOps Foundation aligned knowledge for AI agents: cloud cost (AWS/Azure/GCP/OCI), AI inference economics, Kubernetes, data platforms, allocation, chargeback, ano. It is categorized as a MCP Server with 50 GitHub stars.
cloud-finops-skills is primarily written in Python. It covers topics such as agent-skills, ai-cost-management, aws.
You can find installation instructions and usage details in the cloud-finops-skills GitHub repository at github.com/OptimNow/cloud-finops-skills. The project has 50 stars and 16 forks, indicating an active community.
The top alternatives to cloud-finops-skills on Agent Skills Hub include Lambda-MCP-Server, claude-historian-mcp, awesome-ai-agent-skills. 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: