weibaohui/k8m
by Various
一款轻量级、跨平台的 Mini Kubernetes AI Dashboard，支持大模型+智能体+MCP(支持设置操作权限)，集成多集群管理、智能分析、实时异常检测等功能，支持多架构并可单文件部署，助力高效集群管理与运维优化。
MCP
weibaohui/k8m
Added 1 June 2026
Overview
weibaohui/k8m is a lightweight, cross-platform mini Kubernetes AI dashboard written in Go. It integrates large language model agents with MCP (action permission settings) to deliver multi-cluster management, intelligent analysis, and real-time anomaly detection. The tool is single-file deployable and supports multiple architectures.
Best for
Best for
Kubernetes operators and SREs who want a lightweight, AI-enhanced dashboard with permission management for multi-cluster environments.
Use cases
- Providing a unified dashboard for managing multiple Kubernetes clusters
- Performing intelligent analysis and real-time anomaly detection on cluster resources
- Setting action-level permissions for AI-driven cluster operations via MCP
Notes
weibaohui/k8m is a lightweight, cross-platform mini Kubernetes AI dashboard written in Go. It integrates large language model agents with MCP (action permission settings) to deliver multi-cluster management, intelligent analysis, and real-time anomaly detection. The tool is single-file deployable and supports multiple architectures.
826 stars on GitHub. Last updated 2026-05-30. Licensed MIT.
Use cases
- Providing a unified dashboard for managing multiple Kubernetes clusters
- Performing intelligent analysis and real-time anomaly detection on cluster resources
- Setting action-level permissions for AI-driven cluster operations via MCP
Pros
- Single-file deployment and multi-architecture support simplify setup
- Real-time anomaly detection aids proactive cluster maintenance
- Built-in AI agent with fine-grained permission control for safe automation
Cons
- Limited to Kubernetes-focused use cases; not a general-purpose AI tool
- Relatively small community (826 stars) may mean fewer integrations or support
- Documentation and UI may cater primarily to Chinese-speaking users
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Single-file deployment and multi-architecture support simplify setup
- Real-time anomaly detection aids proactive cluster maintenance
- Built-in AI agent with fine-grained permission control for safe automation
Cons
- Limited to Kubernetes-focused use cases; not a general-purpose AI tool
- Relatively small community (826 stars) may mean fewer integrations or support
- Documentation and UI may cater primarily to Chinese-speaking users
Pairs with
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