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K8m MCP Server

@weibaohui

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基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

weibaohui

投稿者

的太阳 大罗马

K8m MCP Server について

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。

#k8m#kubernetes#ai-dashboard

K8m MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "k8m": {
      "type": "http",
      "url": "http://localhost:3619/sse"
    }
  }
}

K8m MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンでサーバーのエンドポイントに接続し、ツール一覧を取得できます。

概要

What is K8m?

K8m is an AI-driven Mini Kubernetes AI Dashboard (lightweight console tool) designed to simplify cluster management. It integrates with Kubernetes via the kom API client, includes an embedded Qwen2.5-Coder-7B model (with support for DeepSeek-R1-Distill-Qwen-7B), and allows connection to private large language models (including through Ollama). It also functions as a Model Context Protocol (MCP) server, providing 49 built-in MCP tools for multi-cluster operations.

How to use K8m?

Download the latest release from GitHub, run the binary with ./k8m, and access the web UI at http://127.0.0.1:3618. Log in with username k8m and password k8m. Alternatively, deploy via Docker Compose using the provided image registry.cn-hangzhou.aliyuncs.com/minik8m/k8m or install into a Kubernetes cluster with kubectl apply -f deploy/k8m.yaml. Detailed configuration is available in the project documentation.

Key features of K8m

  • Miniaturized design: single executable file.
  • AI-powered: built-in model, MCP integration, and custom LLM support.
  • Multi-cluster management with automatic discovery and heartbeat detection.
  • Role-based access control for clusters, namespaces, and commands.
  • Pod file management: browse, edit, upload, download, delete.
  • Helm chart marketplace with one-click install/upgrade/uninstall.
  • Cluster inspection with scheduled scans, custom Lua rules, and AI summaries.
  • Kubernetes event forwarding to webhooks with filtering.
  • Full API (Swagger) and CRD auto-discovery.

Use cases of K8m

  • Centralized management of multiple Kubernetes clusters (standard k8s, EKS, K3s, kind, k0s).
  • AI-assisted debugging: YAML translation, log analysis, command recommendations.
  • MCP-based tool calling to let large language models control Kubernetes operations.
  • Cluster health monitoring with automated inspections and notifications.
  • Developer self-service: deploy Helm charts, manage pods, and execute shell commands.

よくある質問

1

What is the default login for K8m?

Default username is `k8m` and password is `k8m`. It is recommended to change these after first login and enable two-factor authentication.

2

Does K8m require an external language model?

No. From version 0.0.8, K8m includes a built-in GPT model. You can optionally configure your own self-hosted model or Ollama.

3

What database does K8m support?

K8m supports SQLite, MySQL, and PostgreSQL databases, selected based on configuration.

4

Can K8m be used as an MCP server for other LLM software?

Yes. K8m includes 49 MCP tools for multi-cluster Kubernetes operations and can be used as an MCP server by other large language model applications. Every MCP call is logged.

5

How does K8m handle cluster permissions for MCP?

K8m ties MCP permissions to the user's own cluster permissions. When a large language model invokes an MCP tool, the operation is executed with the corresponding user's authority, preventing privilege escalation.

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