#Container Orchestration MCP Servers

Manage Linode cloud infrastructure. Provision compute instances, manage Kubernetes clusters (LKE), and monitor account details directly from your AI agent.

Automate Kubernetes orchestrations via Argo Workflows. Monitor, list, and inspect active pods, crons, and workflow templates directly from any AI agent.

Manage edge infrastructure via Fly.io. Monitor apps and machines, scale compute horizontally, handle persistent volumes, and run remote commands directly from any AI agent.

Build, test, and deploy using Dagger's programmable CI engine. Execute GraphQL queries, manage containers, and orchestrate pipelines directly from your AI agent.

Orchestrate Kubernetes clusters via Porter. Manage apps, projects, container tags, and enforce rollouts directly with your AI.

Equip your AI to manage Kubernetes environments directly through Rancher, overseeing clusters, namespaces, and active pods.

Integrate your AI securely to RunPod to cleanly quickly provision scalable GPU pods, manage active instances, and inspect serverless endpoints and custom templates natively.

Manage CI/CD and GitOps via Codefresh. Track pipelines, trigger builds, and monitor delivery clusters directly from any AI agent.

Manage self-hosted apps via Dokku. Monitor containers, scale processes, handle environment variables, and stream logs directly from any AI agent.

An AI generated Kubernetes manifests for a payment service. No resource requests or limits. No PodSecurityStandards. Single replica, no PDB. Zero NetworkPolicies. Every pod could reach every other pod. The payment pod got OOM-killed at 3 AM by a logging sidecar with no memory ceiling. This tool forces resource governance, security hardening, reliability design, observability instrumentation, and network restriction on every workload.