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Kubernetes AI Ops Agent MCP Server

@jhzhu89

基本情報

カテゴリ

クラウドとインフラ

ライセンス

MIT

トランスポート

stdio

作者

jhzhu89

Kubernetes AI Ops Agent MCP Server について

AI-powered assistant that enables natural language interactions with Kubernetes clusters. Simplifies DevOps workflows using Model Context Protocol (MCP) servers for executing K8s operations through conversational interfaces.

Kubernetes AI Ops Agent 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": {
    "kubernetes-ai-ops-agent": {
      "command": "docker",
      "args": [
        "build",
        "-t",
        "<YOUR_CONTAINER_REGISTRY>/kubernetes-ai-ops-agent:<TAG>",
        "."
      ]
    }
  }
}

Kubernetes AI Ops Agent 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。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Kubernetes AI Ops Agent?

Kubernetes AI Ops Agent is an AI-powered assistant that helps DevOps engineers and Kubernetes administrators manage Kubernetes clusters through natural language conversations. It leverages Large Language Models (LLMs) and specialized MCP (Model Context Protocol) servers to interpret user intents and execute Kubernetes operations.

How to use Kubernetes AI Ops Agent?

Install dependencies: npm install -g @kubernetes-ai/mcp-server-kubernetes and pip install prometheus-mcp-server. Ensure your Kubernetes kubeconfig is set up, then run chainlit run src/main.py for local development. For production, build a Docker image and deploy via the provided Helm chart with your OpenAI or Azure OpenAI credentials and Prometheus URL.

Key features of Kubernetes AI Ops Agent

  • AI-powered natural language interaction with Kubernetes clusters
  • Tool integration for executing Kubernetes operations
  • Packaged with Docker and Helm charts for easy deployment
  • Web interface built with Chainlit for interactive chat
  • Supports OpenAI and Azure OpenAI models (currently only OpenAI)
  • Integrates Kubernetes and Prometheus MCP servers

Use cases of Kubernetes AI Ops Agent

  • Query cluster state: “Show me all pods in the default namespace”
  • Troubleshoot pods: “Why is my pod in CrashLoopBackOff state?”
  • Retrieve monitoring metrics from Prometheus
  • Automate routine Kubernetes admin tasks via conversation

よくある質問

1

What models does Kubernetes AI Ops Agent support?

Only OpenAI models are supported. You can configure either the OpenAI API directly or Azure OpenAI API.

2

Is Kubernetes AI Ops Agent production-ready?

No, the project is currently experimental and serves as a proof of concept. Features may change significantly.

3

What are the prerequisites for running Kubernetes AI Ops Agent?

You need Python 3.10+, Docker, Helm, access to a Kubernetes cluster with a valid kubeconfig, and the required MCP servers installed.

4

Where does session data live?

Session data is managed by Chainlit’s session storage; for local development it is stored in memory. No external database is required.

5

Can I run Kubernetes AI Ops Agent locally without a container?

Yes, follow the local development installation steps: clone the repo, install dependencies, configure kubeconfig, and run `chainlit run src/main.py`.

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