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