kubernetes-mcp-server — Claude MCP 必备工具中文教程
AI Skill Hub 强烈推荐：kubernetes-mcp-server — Claude MCP 必备工具中文教程 是一款优质的MCP工具。已获得 1.6k 颗 GitHub Star，AI 综合评分 8.6 分，在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案，这是一个值得深入了解的选择。
通过安装 kubernetes-mcp-server — Claude MCP 必备工具中文教程，你的 AI 助手将获得额外的工具调用能力，可以用自然语言直接操控该工具的功能，无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置，永久增强"——配置完成后，每次与 AI 对话时都可以无缝调用这些工具。
在技术实现上，MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信，工具的功能以"工具列表"的形式暴露给 AI 模型，AI 可以按需调用。kubernetes-mcp-server — Claude MCP 必备工具中文教程 提供了结构化的工具调用接口，使 AI 模型能够精确地理解和使用每个功能点，显著降低 AI 在工具使用上的错误率。
与传统的 API 集成相比，MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON，即可让 AI 获得全新能力。AI Skill Hub 将 kubernetes-mcp-server — Claude MCP 必备工具中文教程 评为 AI 评分 8.6 分，属于同类工具中的优质选择。
kubernetes-mcp-server — Claude MCP 必备工具中文教程 是一款遵循 MCP（Model Context Protocol）标准协议的 AI 工具扩展。通过 MCP 协议，它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务，实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用，都可以通过自然语言在 AI 对话中直接触发，极大提升生产效率。
kubernetes-mcp-server — Claude MCP 必备工具中文教程 是一款遵循 MCP（Model Context Protocol）标准协议的 AI 工具扩展。通过 MCP 协议，它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务，实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用，都可以通过自然语言在 AI 对话中直接触发，极大提升生产效率。
- 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
- 提供结构化工具调用接口，显著降低 AI 集成复杂度
- 支持 Claude Desktop 和 Claude Code 无缝接入，开箱即用
- 可与其他 MCP 工具组合叠加，构建完整 AI 工作站
- 轻量无侵入设计，不影响现有系统架构
- 在 Claude Desktop 对话中直接调用本地工具，实现 AI 与系统的深度联动
- 通过自然语言驱动复杂的多步骤自动化任务，代替繁琐手动操作
- 将多个 MCP 工具组合使用，构建个人专属 AI 工作站
# 方式一：通过 Claude Code CLI 一键安装
claude skill install https://github.com/containers/kubernetes-mcp-server
# 方式二：手动配置 claude_desktop_config.json
{
"mcpServers": {
"kubernetes-mcp-server---claude-mcp---------": {
"command": "npx",
"args": ["-y", "kubernetes-mcp-server"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
- 确认已安装 Node.js（v18 或以上版本）
- 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
- 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
- 保存配置文件并重启 Claude 客户端
- 重启后，在对话中即可使用本工具
# 安装后在 Claude 对话中直接使用 # 示例： 用户: 请帮我用 kubernetes-mcp-server — Claude MCP 必备工具中文教程 执行以下任务... Claude: [自动调用 kubernetes-mcp-server — Claude MCP 必备工具中文教程 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入："列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"kubernetes-mcp-server___claude_mcp_________": {
"command": "npx",
"args": ["-y", "kubernetes-mcp-server"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Kubernetes MCP Server
✨ Features | 🚀 Getting Started | 🎥 Demos | ⚙️ Configuration | 🛠️ Tools | 💬 Community | 🧑💻 Development
https://github.com/user-attachments/assets/be2b67b3-fc1c-4d11-ae46-93deba8ed98e
✨ Features <a id="features"></a>
A powerful and flexible Kubernetes Model Context Protocol (MCP) server implementation with support for Kubernetes and OpenShift.
- ✅ Configuration:
- Automatically detect changes in the Kubernetes configuration and update the MCP server.
- View and manage the current Kubernetes
.kube/configor in-cluster configuration. - ✅ Generic Kubernetes Resources: Perform operations on any Kubernetes or OpenShift resource.
- Any CRUD operation (Create or Update, Get, List, Delete).
- ✅ Pods: Perform Pod-specific operations.
- List pods in all namespaces or in a specific namespace.
- Get a pod by name from the specified namespace.
- Delete a pod by name from the specified namespace.
- Show logs for a pod by name from the specified namespace.
- Top gets resource usage metrics for all pods or a specific pod in the specified namespace.
- Exec into a pod and run a command.
- Run a container image in a pod and optionally expose it.
- ✅ Namespaces: List Kubernetes Namespaces.
- ✅ Events: View Kubernetes events in all namespaces or in a specific namespace.
- ✅ Projects: List OpenShift Projects.
- ☸️ Helm:
- Install a Helm chart in the current or provided namespace.
- List Helm releases in all namespaces or in a specific namespace.
- Uninstall a Helm release in the current or provided namespace.
- 🔧 Tekton: Tekton-specific operations that complement generic Kubernetes resource management.
- Pipeline: Start a Tekton Pipeline by creating a PipelineRun.
- PipelineRun: Restart a PipelineRun with the same spec.
- Task: Start a Tekton Task by creating a TaskRun.
- TaskRun: Restart a TaskRun with the same spec, and retrieve TaskRun logs via pod resolution.
- 🔭 Observability: Optional OpenTelemetry distributed tracing and metrics with custom sampling rates. Includes
/statsendpoint for real-time statistics. See OTEL.md.
Unlike other Kubernetes MCP server implementations, this IS NOT just a wrapper around kubectl or helm command-line tools. It is a Go-based native implementation that interacts directly with the Kubernetes API server.
There is NO NEED for external dependencies or tools to be installed on the system. If you're using the native binaries you don't need to have Node or Python installed on your system.
- ✅ Lightweight: The server is distributed as a single native binary for Linux, macOS, and Windows.
- ✅ High-Performance / Low-Latency: Directly interacts with the Kubernetes API server without the overhead of calling and waiting for external commands.
- ✅ Multi-Cluster: Can interact with multiple Kubernetes clusters simultaneously (as defined in your kubeconfig files).
- ✅ Cross-Platform: Available as a native binary for Linux, macOS, and Windows, as well as an npm package, a Python package, and container/Docker image.
- ✅ Configurable: Supports command-line arguments, TOML configuration files, and environment variables.
- ✅ Well tested: The server has an extensive test suite to ensure its reliability and correctness across different Kubernetes environments.
- 📚 Documentation: Comprehensive user documentation including setup guides, configuration reference, and observability.
Requirements
- Access to a Kubernetes cluster.
<details> <summary><b>Claude Code</b></summary>
Follow the dedicated Claude Code getting started guide in our user documentation.
For a secure production setup with dedicated ServiceAccount and read-only access, also review the Kubernetes setup guide.
</details>
🚀 Getting Started <a id="getting-started"></a>
Diagnosing and automatically fixing an OpenShift Deployment
Demo showcasing how Kubernetes MCP server is leveraged by Claude Desktop to automatically diagnose and fix a deployment in OpenShift without any user assistance.
https://github.com/user-attachments/assets/a576176d-a142-4c19-b9aa-a83dc4b8d941
_Vibe Coding_ a simple game and deploying it to OpenShift
In this demo, I walk you through the process of Vibe Coding a simple game using VS Code and how to leverage Podman MCP server and Kubernetes MCP server to deploy it to OpenShift.
<a href="https://www.youtube.com/watch?v=l05jQDSrzVI" target="_blank"> <img src="docs/images/vibe-coding.jpg" alt="Vibe Coding: Build & Deploy a Game on Kubernetes" width="240" /> </a>
Run the Kubernetes MCP server using npx (in case you have npm and node installed)
npx kubernetes-mcp-server@latest --help
Run the Kubernetes MCP server using uvx (in case you have uv and python installed)
uvx kubernetes-mcp-server@latest --help
Compile the project
make build
🎥 Demos <a id="demos"></a>
⚙️ Configuration <a id="configuration"></a>
The Kubernetes MCP server can be configured using command line (CLI) arguments.
You can run the CLI executable either by using npx, uvx, or by downloading the latest release binary.
```shell
Configuration Options
| Option | Description |
|---|---|
--port | Starts the MCP server in Streamable HTTP mode (path /mcp) and Server-Sent Event (SSE) (path /sse) mode and listens on the specified port . |
--log-level | Sets the logging level (values [from 0-9](https://github.com/kubernetes/community/blob/master/contributors/devel/sig-instrumentation/logging.md)). Similar to [kubectl logging levels](https://kubernetes.io/docs/reference/kubectl/quick-reference/#kubectl-output-verbosity-and-debugging). |
--config | (Optional) Path to the main TOML configuration file. See [Configuration Reference](docs/configuration.md) for details. |
--config-dir | (Optional) Path to drop-in configuration directory. Files are loaded in lexical (alphabetical) order. Defaults to conf.d relative to the main config file if --config is specified. See [Configuration Reference](docs/configuration.md) for details. |
--kubeconfig | Path to the Kubernetes configuration file. If not provided, it will try to resolve the configuration (in-cluster, default location, etc.). |
--list-output | Output format for resource list operations (one of: yaml, table) (default "table") |
--read-only | If set, the MCP server will run in read-only mode, meaning it will not allow any write operations (create, update, delete) on the Kubernetes cluster. This is useful for debugging or inspecting the cluster without making changes. |
--disable-destructive | If set, the MCP server will disable all destructive operations (delete, update, etc.) on the Kubernetes cluster. This is useful for debugging or inspecting the cluster without accidentally making changes. This option has no effect when --read-only is used. |
--stateless | If set, the MCP server will run in stateless mode, disabling tool and prompt change notifications. This is useful for container deployments, load balancing, and serverless environments where maintaining client state is not desired. |
--toolsets | Comma-separated list of toolsets to enable. Check the [🛠️ Tools and Functionalities](#tools-and-functionalities) section for more information. |
--disable-multi-cluster | If set, the MCP server will disable multi-cluster support and will only use the current context from the kubeconfig file. This is useful if you want to restrict the MCP server to a single cluster. |
--cluster-provider | Cluster provider strategy to use (one of: kubeconfig, in-cluster, kcp, disabled). If not set, the server will auto-detect based on the environment. |
Note: Most CLI options have equivalent TOML configuration fields. The--disable-multi-clusterflag is equivalent to settingcluster_provider_strategy = "disabled"in TOML. See the Configuration Reference for all TOML options.
TOML Configuration Files
For complex or persistent configurations, use TOML configuration files instead of CLI arguments:
kubernetes-mcp-server --config /etc/kubernetes-mcp-server/config.tomlExample configuration:
```toml log_level = 2 read_only = true toolsets = ["core", "config", "helm", "kubevirt"]
VS Code / VS Code Insiders
Install the Kubernetes MCP server extension in VS Code Insiders by pressing the following link:
<img src="https://img.shields.io/badge/VS_Code-VS_Code?style=flat-square&label=Install%20Server&color=0098FF" alt="Install in VS Code"> <img alt="Install in VS Code Insiders" src="https://img.shields.io/badge/VS_Code_Insiders-VS_Code_Insiders?style=flat-square&label=Install%20Server&color=24bfa5">
Alternatively, you can install the extension manually by running the following command:
```shell
For VS Code
code --add-mcp '{"name":"kubernetes","command":"npx","args":["kubernetes-mcp-server@latest"]}'
For VS Code Insiders
code-insiders --add-mcp '{"name":"kubernetes","command":"npx","args":["kubernetes-mcp-server@latest"]}' ```
Supercharge GitHub Copilot with Kubernetes MCP Server in VS Code - One-Click Setup!
In this demo, I'll show you how to set up Kubernetes MCP server in VS code just by clicking a link.
<a href="https://youtu.be/AI4ljYMkgtA" target="_blank"> <img src="docs/images/kubernetes-mcp-server-github-copilot.jpg" alt="Supercharge GitHub Copilot with Kubernetes MCP Server in VS Code - One-Click Setup!" width="240" /> </a>
- 需要让 Claude / Cursor 操作本地工具的 AI 工程师
- 构建多智能体协作系统的 Agent 开发者
- 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC，避免暴露公网
- 生产部署优先使用 Docker Compose 隔离依赖，并挂载 volume 持久化数据
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- MCP 配置路径拼错或权限不足，重启 Claude Desktop 才生效
- 容器内无法访问宿主机 localhost — 使用 host.docker.internal
- Docker：kubernetes-mcp-server 提供官方镜像，docker compose up 一键启动
- CLI：直接 npm install -g / pip install，命令行调用
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
- 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
- 提供结构化工具调用接口，显著降低 AI 集成复杂度
- 支持 Claude Desktop 和 Claude Code 无缝接入，开箱即用
- 可与其他 MCP 工具组合叠加，构建完整 AI 工作站
- 轻量无侵入设计，不影响现有系统架构
- 在 Claude Desktop 对话中直接调用本地工具，实现 AI 与系统的深度联动
- 通过自然语言驱动复杂的多步骤自动化任务，代替繁琐手动操作
- 将多个 MCP 工具组合使用，构建个人专属 AI 工作站
- +Apache-2.0 协议，可免费商用
- +标准化 MCP 协议，生态互联性强
- +与 Claude 官方生态无缝对接
- +即插即用，配置简单快捷
- −依赖 Claude 客户端，非 Claude 用户无法使用
- −MCP 协议仍在持续演进，接口可能变更
- −需要一定的配置步骤
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议，可商用，需保留版权声明和 NOTICE 文件，含专利授权条款。
总体来看，kubernetes-mcp-server — Claude MCP 必备工具中文教程 是一款质量优秀的MCP工具，在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态，建议收藏备用，结合自身场景选择合适时机引入使用。
| 原始名称 | kubernetes-mcp-server |
| 原始描述 | Model Context Protocol (MCP) server for Kubernetes and OpenShift |
| Topics | containerscontextkuberneteskubernetes-mcpmcpmodel |
| GitHub | https://github.com/containers/kubernetes-mcp-server |
| License | Apache-2.0 |
| 语言 | Go |
收录时间：2026-05-22 · 更新时间：2026-05-22 · License：Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。