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Kubernetes AI Ops Agent MCP Server

@jhzhu89

代码仓库

基本信息

分类

云与基础设施

许可证

MIT

传输方式

stdio

作者

jhzhu89

关于 Kubernetes AI Ops Agent MCP Server

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

Kubernetes AI Ops Agent MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Kubernetes AI Ops Agent MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

常见问题

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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