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 aliyun · MCP Server · ★ 117
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is alibabacloud-ack-mcp-server safe to install? View the security audit →
阿里云容器服务 MCP Server (ack-mcp-server) 阿里云容器服务 MCP Server 工具集: ack-mcp-server。 将 ACK 集群/资源管理、Kubernetes 原生操作与容器场景的可观测性能力、安全审计、诊断巡检等运维能力统一为 AI 原生的标准化工具集。 本工具集的能力被阿里云容器服务智能助手功能集成。也可支持三方 AI Agent (kubectl-ai、QWen Code、Claude Code、Cursor、Gemini CLI、VS Code等)或自动化系统调用集成，基于 MCP（Model Context Protocol）协议。 实现支持通过自然语言与 AI 助手交互，完成复杂的容器运维任务。帮助构建用户自己的容器场景 AIOps 运维体系。 概述 & 功能简介 如何使用 & 部署 [3. 如何本地开发运行](#-3-如何本地开
| Stars | 117 |
| Forks | 15 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 67.5603299830593/100 |
| Open Issues | 8 |
| Last Updated | 2026-07-31 |
| Created | 2025-09-18 |
| Platforms | k8s, mcp, python |
| Est. Tokens | ~16k |
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alibabacloud-ack-mcp-server is Alibaba Cloud's ack-mcp-server unifies container operations capabilities, enabling AI assistants and third-party AI agents to perform complex tasks via natural language through the MCP protocol, empow. It is categorized as a MCP Server with 117 GitHub stars.
alibabacloud-ack-mcp-server is primarily written in Python. It covers topics such as agent, ai, aiops.
You can find installation instructions and usage details in the alibabacloud-ack-mcp-server GitHub repository at github.com/aliyun/alibabacloud-ack-mcp-server. The project has 117 stars and 15 forks, indicating an active community.
alibabacloud-ack-mcp-server is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to alibabacloud-ack-mcp-server on Agent Skills Hub include clanker, aura, siclaw. 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: