Governed Kubernetes ops — 15 MCP tools with audit, budget, undo guards.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-aiops-tools-k8s-aiops": {
"command": "<see-readme>",
"args": []
}
}
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Disclaimer: This is a community-maintained open-source project and is not > affiliated with, endorsed by, or sponsored by the Cloud Native Computing > Foundation, the Kubernetes project, or k3s/Rancher. "Kubernetes" and "k3s" are > trademarks of their respective owners. Source code is publicly auditable at > github.com/AIops-tools/K8s-AIops under
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Disclaimer: This is a community-maintained open-source project and is not affiliated with, endorsed by, or sponsored by the Cloud Native Computing Foundation, the Kubernetes project, or k3s/Rancher. "Kubernetes" and "k3s" are trademarks of their respective owners. Source code is publicly auditable at github.com/AIops-tools/K8s-AIops under the MIT license.
Governed Kubernetes operations for AI agents — 51 MCP tools, every one wrapped
with the bundled @governed_tool harness: a local unified audit log under
~/.k8s-aiops/, policy engine, token/runaway budget guard, undo-token recording, and
graduated-autonomy risk tiers. Coverage spans pods, deployments, statefulsets,
daemonsets, replicasets, jobs/cronjobs, services, ingresses, endpoints,
configmaps, secrets (names/keys only), PVCs/PVs/storageclasses, nodes, namespaces,
events, rollouts (status/history/undo/pause/resume/set-image), pod/node describe,
pod/node top, and a cluster health summary.
Standalone: the governance harness is bundled in the package (
k8s_aiops.governance) — k8s-aiops has no external skill-family dependency. Preview: common cluster operations, not yet exhaustive.
Any cluster a kubeconfig can reach: standard Kubernetes, k3s, EKS, GKE, AKS, kind, minikube. Authentication (client certs, tokens, EKS/GKE/AKS exec plugins) is delegated entirely to the kubeconfig.
uv tool install k8s-aiops
# Friendly onboarding wizard — registers your kube contexts as named targets:
k8s-aiops init
# Or skip it — uses your current kube-context out of the box:
k8s-aiops doctor
k8s-aiops pod list
k8s-aiops deployment list -n default
To define named targets (multiple clusters/contexts), create
~/.k8s-aiops/config.yaml:
targets:
- name: prod # used as -t prod
context: prod-eks # a context in your kubeconfig (omit for current-context)
namespace: default # optional default namespace
# kubeconfig: /path/to/alt/kubeconfig # optional explicit path
- name: lab
context: k3s-lab
No secrets live in this file — credentials come from the kubeconfig.
{
"command": "k8s-aiops",
"args": ["mcp"],
"env": { "K8S_AIOPS_CONFIG": "~/.k8s-aiops/config.yaml" }
}
~/.k8s-aiops/audit.db (local SQLite; relocate with
K8S_AIOPS_HOME).scale_deployment →
scale-back to previous; cordon_node ↔ uncordon_node).delete_deployment is risk_level=high; CLI destructive commands require double
confirmation and support --dry-run.sanitize() (prompt-injection defense).See skills/k8s-aiops/SKILL.md and SECURITY.md for details.
| If you want… | Use |
|---|---|
| Kubernetes pods / deployments / nodes | k8s-aiops (this) |
| Hypervisor VM lifecycle | a hypervisor ops skill |
| Backup & restore | a backup ops skill |
This is a preview — coverage is intentionally focused. Missing a device, action, or feature you need? Open an issue or pull request at github.com/AIops-tools/K8s-AIops — feature requests, contributions, and comments are all welcome.