Source: kubestellar/kubestellar-mcp/commands/deploy.md

Deploy

Deploy an app to multiple clusters with smart placement.

Usage

Deploy a workload to clusters. You can specify target clusters explicitly or let kubestellar-deploy find matching clusters based on requirements.

Examples

  • “Deploy this nginx deployment to all clusters”
  • “Deploy my ML model to clusters with GPUs”
  • “Deploy this app to clusters with at least 16Gi memory”
  • “Do a dry run of deploying this manifest”

What it does

  1. Finds clusters matching your requirements (or uses all clusters)
  2. Applies the manifest to each target cluster
  3. Reports success/failure per cluster

MCP Tools Used

  • deploy_app - Deploy an app to clusters
  • find_clusters_for_workload - Find clusters matching requirements
  • list_cluster_capabilities - See what each cluster can run

Implementation

Use the deploy_app tool with:

  • manifest: The Kubernetes YAML manifest
  • clusters: Optional list of target clusters
  • gpu_type: Optional GPU type requirement (e.g., “nvidia.com/gpu”)
  • min_gpu: Optional minimum GPU count
  • dry_run: Set to true to preview without applying

Smart Placement

If you don’t specify clusters, kubestellar-deploy can:

  • Deploy to all clusters
  • Filter to clusters with specific GPU types
  • Filter to clusters with minimum CPU/memory
  • Filter to clusters with specific node labels