MCP Server Kubernetes
MCP Server that can connect to a Kubernetes cluster and manage it. Supports loading kubeconfig from multiple sources in priority order.
https://github.com/user-attachments/assets/f25f8f4e-4d04-479b-9ae0-5dac452dd2ed
Installation & Usage
Prerequisites
Before using this MCP server with any tool, make sure you have:
- kubectl installed and in your PATH
- A valid kubeconfig file with contexts configured
- Access to a Kubernetes cluster configured for kubectl (e.g. minikube, Rancher Desktop, GKE, etc.)
- Helm v3 installed and in your PATH (no Tiller required). Optional if you don't plan to use Helm.
You can verify your connection by running kubectl get pods in a terminal to ensure you can connect to your cluster without credential issues.
By default, the server loads kubeconfig from ~/.kube/config. For additional authentication options (environment variables, custom paths, etc.), see ADVANCED_README.md.
Claude Code
Add the MCP server to Claude Code using the built-in command:
claude mcp add kubernetes -- npx mcp-server-kubernetes
This will automatically configure the server in your Claude Code MCP settings.
Claude Desktop
Add the following configuration to your Claude Desktop config file:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["mcp-server-kubernetes"]
}
}
}
VS Code
For VS Code integration, you can use the MCP server with extensions that support the Model Context Protocol:
- Install a compatible MCP extension (such as Claude Dev or similar MCP clients)
- Configure the extension to use this server:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["mcp-server-kubernetes"],
"description": "Kubernetes cluster management and operations"
}
}
}
Cursor
Cursor supports MCP servers through its AI integration. Add the server to your Cursor MCP configuration:
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["mcp-server-kubernetes"]
}
}
}
The server will automatically connect to your current kubectl context. You can verify the connection by asking the AI assistant to list your pods or create a test deployment.
Usage with mcp-chat
mcp-chat is a CLI chat client for MCP servers. You can use it to interact with the Kubernetes server.
npx mcp-chat --server "npx mcp-server-kubernetes"
Alternatively, pass it your existing Claude Desktop configuration file from above (Linux should pass the correct path to config):
Mac:
npx mcp-chat --config "~/Library/Application Support/Claude/claude_desktop_config.json"
Windows:
npx mcp-chat --config "%APPDATA%\Claude\claude_desktop_config.json"
Features
- Connect to a Kubernetes cluster
- Unified kubectl API for managing resources
- Get or list resources with
kubectl_get - Describe resources with
kubectl_describe - List resources with
kubectl_get - Create resources with
kubectl_create - Apply YAML manifests with
kubectl_apply - Delete resources with
kubectl_delete - Get logs with
kubectl_logs - Manage kubectl contexts with
kubectl_context - Explain Kubernetes resources with
explain_resource - List API resources with
list_api_resources - Scale resources with
kubectl_scale - Update field(s) of a resource with
kubectl_patch - Manage deployment rollouts with
kubectl_rollout - Execute any kubectl command with
kubectl_generic - Verify connection with
ping
- Get or list resources with
- Advanced operations
- Scale deployments with
kubectl_scale(replaces legacyscale_deployment) - Port forward to pods and services with
port_forward - Run Helm operations
- Install, upgrade, and uninstall charts
- Support for custom values, repositories, and versions
- Template-based installation (
helm_template_apply) to bypass authentication issues - Template-based uninstallation (
helm_template_uninstall) to bypass authentication issues
- Pod cleanup operations
- Clean up problematic pods (
cleanup_pods) in states: Evicted, ContainerStatusUnknown, Completed, Error, ImagePullBackOff, CrashLoopBackOff
- Clean up problematic pods (
- Node management operations
- Cordoning, draining, and uncordoning nodes (
node_management) for maintenance and scaling operations
- Cordoning, draining, and uncordoning nodes (
- Scale deployments with
- Troubleshooting Prompt (
k8s-diagnose)- Guides through a systematic Kubernetes troubleshooting flow for pods based on a keyword and optional namespace.
- Non-destructive mode for read and create/update-only access to clusters
- Secrets masking for security (masks sensitive data in
kubectl get secretscommands, does not affect logs)
Prompts
The MCP Kubernetes server includes specialized prompts to assist with common diagnostic operations.
/k8s-diagnose Prompt
This prompt provides a systematic troubleshooting flow for Kubernetes pods. It accepts a keyword to identify relevant pods and an optional namespace to narrow the search.
The prompt's output will guide you through an autonomous troubleshooting flow, providing instructions for identifying issues, collecting evidence, and suggesting remediation steps.
Local Development
Make sure that you have bun installed. Clone the repo & install dependencies:
git clone https://github.com/Flux159/mcp-server-kubernetes.git
cd mcp-server-kubernetes
bun install
Development Workflow
- Start the server in development mode (watches for file changes):
bun run dev
- Run unit tests:
bun run test
- Build the project:
bun run build
- Local Testing with Inspector
npx @modelcontextprotocol/inspector node dist/index.js
# Follow further instructions on terminal for Inspector link
- Local testing with Claude Desktop
{
"mcpServers": {
"mcp-server-kubernetes": {
"command": "node",
"args": ["/path/to/your/mcp-server-kubernetes/dist/index.js"]
}
}
}
- Local testing with mcp-chat
bun run chat
Contributing
See the CONTRIBUTING.md file for details.
Advanced
Non-Destructive Mode
You can run the server in a non-destructive mode that disables all destructive operations (delete pods, delete deployments, delete namespaces, etc.):
ALLOW_ONLY_NON_DESTRUCTIVE_TOOLS=true npx mcp-server-kubernetes
For Claude Desktop configuration with non-destructive mode:
{
"mcpServers": {
"kubernetes-readonly": {
"command": "npx",
"args": ["mcp-server-kubernetes"],
"env": {
"ALLOW_ONLY_NON_DESTRUCTIVE_TOOLS": "true"
}
}
}
}
Commands Available in Non-Destructive Mode
All read-only and resource creation/update operations remain available:
- Resource Information:
kubectl_get,kubectl_describe,kubectl_logs,explain_resource,list_api_resources - Resource Creation/Modification:
kubectl_apply,kubectl_create,kubectl_scale,kubectl_patch,kubectl_rollout - Helm Operations:
install_helm_chart,upgrade_helm_chart,helm_template_apply,helm_template_uninstall - Connectivity:
port_forward,stop_port_forward - Context Management:
kubectl_context
Commands Disabled in Non-Destructive Mode
The following destructive operations are disabled:
kubectl_delete: Deleting any Kubernetes resourcesuninstall_helm_chart: Uninstalling Helm chartscleanup: Cleanup of managed resourcescleanup_pods: Cleaning up problematic podsnode_management: Node management operations (can drain nodes)kubectl_generic: General kubectl command access (may include destructive operations)
Helm Template Apply Tool
The helm_template_apply tool provides an alternative way to install Helm charts that bypasses authentication issues commonly encountered with certain Kubernetes configurations. This tool is particularly useful when you encounter errors like:
WARNING: Kubernetes configuration file is group-readable. This is insecure.
Error: INSTALLATION FAILED: Kubernetes cluster unreachable: exec plugin: invalid apiVersion "client.authentication.k8s.io/v1alpha1"
Instead of using helm install directly, this tool:
- Uses
helm templateto generate YAML manifests from the Helm chart - Applies the generated YAML using
kubectl apply - Handles namespace creation and cleanup automatically
Usage Example
{
"name": "helm_template_apply",
"arguments": {
"name": "events-exporter",
"chart": ".",
"namespace": "kube-event-exporter",
"valuesFile": "values.yaml",
"createNamespace": true
}
}
This is equivalent to running:
helm template events-exporter . -f values.yaml > events-exporter.yaml
kubectl create namespace kube-event-exporter
kubectl apply -f events-exporter.yaml -n kube-event-exporter
Parameters
name: Release name for the Helm chartchart: Chart name or path to chart directoryrepo: Chart repository URL (optional if using local chart path)namespace: Kubernetes namespace to deploy tovalues: Chart values as an object (optional)valuesFile: Path to values.yaml file (optional, alternative to values object)createNamespace: Whether to create the namespace if it doesn't exist (default: true)
Pod Cleanup with Existing Tools
Pod cleanup can be achieved using the existing kubectl_get and kubectl_delete tools with field selectors. This approach leverages standard Kubernetes functionality without requiring dedicated cleanup tools.
Identifying Problematic Pods
Use kubectl_get with field selectors to identify pods in problematic states:
Get failed pods:
{
"name": "kubectl_get",
"arguments": {
"resourceType": "pods",
"namespace": "default",
"fieldSelector": "status.phase=Failed"
}
}
Get completed pods:
{
"name": "kubectl_get",
"arguments": {
"resourceType": "pods",
"namespace": "default",
"fieldSelector": "status.phase=Succeeded"
}
}
Get pods with specific conditions:
{
"name": "kubectl_get",
"arguments": {
"resourceType": "pods",
"namespace": "default",
"fieldSelector": "status.conditions[?(@.type=='Ready')].status=False"
}
}
Deleting Problematic Pods
Use kubectl_delete with field selectors to delete pods in problematic states:
Delete failed pods:
{
"name": "kubectl_delete",
"arguments": {
"resourceType": "pods",
"namespace": "default",
"fieldSelector": "status.phase=Failed",
"force": true,
"gracePeriodSeconds": 0
}
}
Delete completed pods:
{
"name": "kubectl_delete",
"arguments": {
"resourceType": "pods",
"namespace": "default",
"fieldSelector": "status.phase=Succeeded",
"force": true,
"gracePeriodSeconds": 0
}
}
Workflow
- First, identify problematic pods using
kubectl_getwith appropriate field selectors - Review the list of pods in the response
- Delete the pods using
kubectl_deletewith the same field selectors
Available Field Selectors
status.phase=Failed- Pods that have failedstatus.phase=Succeeded- Pods that have completed successfullystatus.phase=Pending- Pods that are pendingstatus.conditions[?(@.type=='Ready')].status=False- Pods that are not ready
Safety Features
- Field selectors: Target specific pod states precisely
- Force deletion: Use
force=trueandgracePeriodSeconds=0for immediate deletion - Namespace isolation: Target specific namespaces or use
allNamespaces=true - Standard kubectl: Uses well-established Kubernetes patterns
Node Management Tool
The node_management tool provides comprehensive node management capabilities for Kubernetes clusters, including cordoning, draining, and uncordoning operations. This is essential for cluster maintenance, scaling, and troubleshooting.
Operations Available
list: List all nodes with their status and schedulabilitycordon: Mark a node as unschedulable (no new pods will be scheduled)drain: Safely evict all pods from a node and mark it as unschedulableuncordon: Mark a node as schedulable again
Usage Examples
1. List all nodes:
{
"name": "node_management",
"arguments": {
"operation": "list"
}
}
2. Cordon a node (mark as unschedulable):
{
"name": "node_management",
"arguments": {
"operation": "cordon",
"nodeName": "worker-node-1"
}
}
3. Drain a node (dry run first):
{
"name": "node_management",
"arguments": {
"operation": "drain",
"nodeName": "worker-node-1",
"dryRun": true
}
}
4. Drain a node (with confirmation):
{
"name": "node_management",
"arguments": {
"operation": "drain",
"nodeName": "worker-node-1",
"dryRun": false,
"confirmDrain": true,
"force": true,
"ignoreDaemonsets": true,
"timeout": "5m"
}
}
5. Uncordon a node:
{
"name": "node_management",
"arguments": {
"operation": "uncordon",
"nodeName": "worker-node-1"
}
}
Drain Operation Parameters
force: Force the operation even if there are pods not managed by controllersgracePeriod: Period of time in seconds given to each pod to terminate gracefullydeleteLocalData: Delete local data even if emptyDir volumes are usedignoreDaemonsets: Ignore DaemonSet-managed pods (default: true)timeout: The length of time to wait before giving up (e.g., '5m', '1h')dryRun: Show what would be done without actually doing itconfirmDrain: Explicit confirmation to drain the node (required for actual draining)
Safety Features
- Dry run by default: Drain operations default to dry run to show what would be done
- Explicit confirmation: Drain operations require
confirmDrain=trueto proceed - Status tracking: Shows node status before and after operations
- Timeout protection: Configurable timeouts to prevent hanging operations
- Graceful termination: Configurable grace periods for pod termination
Common Use Cases
- Cluster Maintenance: Cordon nodes before maintenance, drain them, perform maintenance, then uncordon
- Node Scaling: Drain nodes before removing them from the cluster
- Troubleshooting: Isolate problematic nodes by cordoning them
- Resource Management: Drain nodes to redistribute workload
For additional advanced features, see the ADVANCED_README.md.
Architecture
See this DeepWiki link for a more indepth architecture overview created by Devin.
This section describes the high-level architecture of the MCP Kubernetes server.
Request Flow
The sequence diagram below illustrates how requests flow through the system:
sequenceDiagram
participant Client
participant Transport as Transport Layer
participant Server as MCP Server
participant Filter as Tool Filter
participant Handler as Request Handler
participant K8sManager as KubernetesManager
participant K8s as Kubernetes API
Note over Transport: StdioTransport or<br>SSE Transport
Client->>Transport: Send Request
Transport->>Server: Forward Request
alt Tools Request
Server->>Filter: Filter available tools
Note over Filter: Remove destructive tools<br>if in non-destructive mode
Filter->>Handler: Route to tools handler
alt kubectl operations
Handler->>K8sManager: Execute kubectl operation
K8sManager->>K8s: Make API call
else Helm operations
Handler->>K8sManager: Execute Helm operation
K8sManager->>K8s: Make API call
else Port Forward operations
Handler->>K8sManager: Set up port forwarding
K8sManager->>K8s: Make API call
end
K8s-->>K8sManager: Return result
K8sManager-->>Handler: Process response
Handler-->>Server: Return tool result
else Resource Request
Server->>Handler: Route to resource handler
Handler->>K8sManager: Get resource data
K8sManager->>K8s: Query API
K8s-->>K8sManager: Return data
K8sManager-->>Handler: Format response
Handler-->>Server: Return resource data
end
Server-->>Transport: Send Response
Transport-->>Client: Return Final Response
See this DeepWiki link for a more indepth architecture overview created by Devin.
Publishing new release
Go to the releases page, click on "Draft New Release", click "Choose a tag" and create a new tag by typing out a new version number using "v{major}.{minor}.{patch}" semver format. Then, write a release title "Release v{major}.{minor}.{patch}" and description / changelog if necessary and click "Publish Release".
This will create a new tag which will trigger a new release build via the cd.yml workflow. Once successful, the new release will be published to npm. Note that there is no need to update the package.json version manually, as the workflow will automatically update the version number in the package.json file & push a commit to main.
Not planned
Adding clusters to kubectx.
Star History
🖊️ Cite
If you find this repo useful, please cite:
@software{Patel_MCP_Server_Kubernetes_2024,
author = {Patel, Paras and Sonwalkar, Suyog},
month = jul,
title = {{MCP Server Kubernetes}},
url = {https://github.com/Flux159/mcp-server-kubernetes},
version = {2.5.0},
year = {2024}
}