containers/kubernetes-mcp-server

✨ Features | 🚀 Getting Started | 🎥 Demos | ⚙️ Configuration | 🛠️ Tools | 💬 Community | 🧑‍💻 Development
https://github.com/user-attachments/assets/be2b67b3-fc1c-4d11-ae46-93deba8ed98e
✨ Features
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/config or 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, cancel, troubleshoot, and retrieve PipelineRun logs.
- **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 /stats endpoint 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.
🚀 Getting Started
Requirements
- Access to a Kubernetes cluster.
Claude Code
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.
Claude Desktop
Using npx
If you have npm installed, this is the fastest way to get started with kubernetes-mcp-server on Claude Desktop.
Open your claude_desktop_config.json and add the mcp server to the list of mcpServers:
VS Code / VS Code Insiders
Install the Kubernetes MCP server extension in VS Code Insiders by pressing the following link:
Alternatively, you can install the extension manually by running the following command:
Cursor
Install the Kubernetes MCP server extension in Cursor by pressing the following link:
Alternatively, you can install the extension manually by editing the mcp.json file:
Goose CLI
Goose CLI is the easiest (and cheapest) way to get rolling with artificial intelligence (AI) agents.
Using npm
If you have npm installed, this is the fastest way to get started with kubernetes-mcp-server.
Open your goose config.yaml and add the mcp server to the list of mcpServers: