Agent skill

k8s-capi

Cluster API lifecycle management for provisioning, scaling, and upgrading Kubernetes clusters. Use when managing cluster infrastructure or multi-cluster operations.

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Install this agent skill to your Project

npx add-skill https://github.com/rohitg00/kubectl-mcp-server/tree/main/kubernetes-skills/claude/k8s-capi

Metadata

Additional technical details for this skill

tools
11
author
rohitg00
version
1.0.0
category
infrastructure

SKILL.md

Cluster API Lifecycle Management

Manage Kubernetes clusters using kubectl-mcp-server's Cluster API tools (11 tools).

When to Apply

Use this skill when:

  • User mentions: "Cluster API", "CAPI", "cluster lifecycle", "machine", "workload cluster"
  • Operations: provisioning clusters, scaling nodes, upgrading Kubernetes versions
  • Keywords: "provision cluster", "scale workers", "machine deployment", "cluster class"

Priority Rules

Priority Rule Impact Tools
1 Detect CAPI installation first CRITICAL capi_detect_tool
2 Check cluster phase before operations HIGH capi_cluster_get_tool
3 Monitor machines during scaling HIGH capi_machines_list_tool
4 Get kubeconfig after provisioning MEDIUM capi_cluster_kubeconfig_tool

Quick Reference

Task Tool Example
Detect CAPI capi_detect_tool capi_detect_tool()
List clusters capi_clusters_list_tool capi_clusters_list_tool(namespace)
Get cluster kubeconfig capi_cluster_kubeconfig_tool capi_cluster_kubeconfig_tool(name, namespace)
Scale workers capi_machinedeployment_scale_tool capi_machinedeployment_scale_tool(name, namespace, replicas)

Check Installation

python
capi_detect_tool()

List Clusters

python
# List all CAPI clusters
capi_clusters_list_tool(namespace="default")

# Shows:
# - Cluster name
# - Phase (Provisioning, Provisioned, Deleting)
# - Infrastructure ready
# - Control plane ready

Get Cluster Details

python
capi_cluster_get_tool(name="my-cluster", namespace="default")

# Shows:
# - Spec (control plane, infrastructure)
# - Status (phase, conditions)
# - Network configuration

Get Cluster Kubeconfig

python
# Get kubeconfig for workload cluster
capi_cluster_kubeconfig_tool(name="my-cluster", namespace="default")

# Returns kubeconfig to access the cluster

Machines

List Machines

python
capi_machines_list_tool(namespace="default")

# Shows:
# - Machine name
# - Cluster
# - Phase (Running, Provisioning, Failed)
# - Provider ID
# - Version

Get Machine Details

python
capi_machine_get_tool(name="my-cluster-md-0-xxx", namespace="default")

Machine Deployments

List Machine Deployments

python
capi_machinedeployments_list_tool(namespace="default")

# Shows:
# - Deployment name
# - Cluster
# - Replicas (ready/total)
# - Version

Scale Machine Deployment

python
# Scale worker nodes
capi_machinedeployment_scale_tool(
    name="my-cluster-md-0",
    namespace="default",
    replicas=5
)

Machine Sets

python
capi_machinesets_list_tool(namespace="default")

Machine Health Checks

python
capi_machinehealthchecks_list_tool(namespace="default")

# Health checks automatically remediate unhealthy machines

Cluster Classes

python
# List cluster templates
capi_clusterclasses_list_tool(namespace="default")

# ClusterClasses define reusable cluster configurations

Create Cluster

python
kubectl_apply(manifest="""
apiVersion: cluster.x-k8s.io/v1beta1
kind: Cluster
metadata:
  name: my-cluster
  namespace: default
spec:
  clusterNetwork:
    pods:
      cidrBlocks:
      - 192.168.0.0/16
    services:
      cidrBlocks:
      - 10.96.0.0/12
  controlPlaneRef:
    apiVersion: controlplane.cluster.x-k8s.io/v1beta1
    kind: KubeadmControlPlane
    name: my-cluster-control-plane
  infrastructureRef:
    apiVersion: infrastructure.cluster.x-k8s.io/v1beta1
    kind: AWSCluster
    name: my-cluster
""")

Create Machine Deployment

python
kubectl_apply(manifest="""
apiVersion: cluster.x-k8s.io/v1beta1
kind: MachineDeployment
metadata:
  name: my-cluster-md-0
  namespace: default
spec:
  clusterName: my-cluster
  replicas: 3
  selector:
    matchLabels:
      cluster.x-k8s.io/cluster-name: my-cluster
  template:
    spec:
      clusterName: my-cluster
      version: v1.28.0
      bootstrap:
        configRef:
          apiVersion: bootstrap.cluster.x-k8s.io/v1beta1
          kind: KubeadmConfigTemplate
          name: my-cluster-md-0
      infrastructureRef:
        apiVersion: infrastructure.cluster.x-k8s.io/v1beta1
        kind: AWSMachineTemplate
        name: my-cluster-md-0
""")

Cluster Lifecycle Workflows

Provision New Cluster

python
1. kubectl_apply(cluster_manifest)
2. capi_clusters_list_tool(namespace)  # Wait for Provisioned
3. capi_cluster_kubeconfig_tool(name, namespace)  # Get access

Scale Workers

python
1. capi_machinedeployments_list_tool(namespace)
2. capi_machinedeployment_scale_tool(name, namespace, replicas)
3. capi_machines_list_tool(namespace)  # Monitor

Upgrade Cluster

python
1. # Update control plane version
2. # Update machine deployment version
3. capi_machines_list_tool(namespace)  # Monitor rollout

Troubleshooting

Cluster Stuck Provisioning

python
1. capi_cluster_get_tool(name, namespace)  # Check conditions
2. capi_machines_list_tool(namespace)  # Check machine status
3. get_events(namespace)  # Check events
4. # Check infrastructure provider logs

Machine Failed

python
1. capi_machine_get_tool(name, namespace)
2. get_events(namespace)
3. # Common issues:
   # - Cloud provider quota
   # - Invalid machine template
   # - Network issues

Related Skills

  • k8s-multicluster - Multi-cluster operations
  • k8s-operations - kubectl operations

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