Kubernetes AI Ops Agent

Name: Kubernetes AI Ops Agent
Author: jhzhu89

@jhzhu89

Kubernetes AI Ops Agent 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 #mcp #prometheus #chainlit #model-context-protocol #openai-agent-sdk

基本情報

カテゴリ

クラウドとインフラ

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

jhzhu89

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>",
        "."
      ]
    }
  }
}

ツール

ツールは検出されませんでした

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

FAQ from Kubernetes AI Ops Agent

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.

Is Kubernetes AI Ops Agent production-ready?

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

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.

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.

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.

「クラウドとインフラ」の他のコンテンツ

Query | MCP server for Supabase

alexander-zuev

Query MCP enables end-to-end management of Supabase via chat interface: read & write query executions, management API support, automatic migration versioning, access to logs and much more.

828

Terraform MCP Server

hashicorp

The Terraform MCP Server provides seamless integration with Terraform ecosystem, enabling advanced automation and interaction capabilities for Infrastructure as Code (IaC) development.

1.5K