kubestellar-console

Multi-cluster Kubernetes dashboard with AI-powered operations via MCP server and 10+ built-in agent skills

5 stars

Best use case

kubestellar-console is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Multi-cluster Kubernetes dashboard with AI-powered operations via MCP server and 10+ built-in agent skills

Teams using kubestellar-console should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/kubestellar-console/SKILL.md --create-dirs "https://raw.githubusercontent.com/FrancoStino/opencode-skills-collection/main/bundled-skills/kubestellar-console/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/kubestellar-console/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How kubestellar-console Compares

Feature / Agentkubestellar-consoleStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Multi-cluster Kubernetes dashboard with AI-powered operations via MCP server and 10+ built-in agent skills

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# KubeStellar Console

## Overview

KubeStellar Console is an open-source multi-cluster Kubernetes dashboard (CNCF project) with AI-powered operations. It ships with `kc-agent`, an MCP server that bridges coding agents to kubeconfig and Kubernetes APIs, plus 10+ built-in agent skills for development, testing, and operations.

## When to Use This Skill

- Use when managing multiple Kubernetes clusters across edge and cloud
- Use when you need AI-assisted Kubernetes troubleshooting and debugging
- Use when running performance tests, cache compliance checks, or CI debugging on a Kubernetes dashboard
- Use when integrating with CNCF projects (Argo, Kyverno, Istio, and 20+ others)

## How It Works

### Step 1: Install kc-agent

```bash
brew tap kubestellar/tap && brew install kc-agent
```

### Step 2: Start the MCP server

```bash
kc-agent
```

This bridges the active kubeconfig context to any MCP-compatible coding agent. Do not start it from a cluster-admin or write-capable context unless the user explicitly accepts that risk.

### Step 3: Use built-in agent skills

The project ships with agent skills accessible via `CLAUDE.md` and `AGENTS.md`:

- **@perf-test** — Dashboard performance testing and TTFI analysis
- **@cache-test** — Card cache compliance testing (IndexedDB warm return)
- **@nav-test** — Navigation performance testing
- **@ui-compliance-test** — Card loading compliance (8 criteria, 150+ cards)
- **@ci-status** — CI pipeline monitoring and status checks
- **@rca** — Root cause analysis for CI/test failures
- **@tdd** — Test-driven development workflow
- **@k8s-debug** — Kubernetes debugging and troubleshooting

## Key Features

- Multi-cluster management across edge and cloud
- Real-time streaming observability
- 20+ CNCF project integrations (Argo, Kyverno, Istio, etc.)
- GitHub OAuth authentication
- Supply chain security (SBOM, SLSA)
- SQLite WASM caching with stale-while-revalidate pattern
- 15+ themes with dark/light mode

## Security & Safety Notes

- **Critical risk:** `kc-agent` bridges your active kubeconfig context to MCP-compatible agents. If that context carries cluster-admin, write permissions, or secret read access, agents inherit those capabilities.
- **Do not rely on RBAC objects alone:** creating a ServiceAccount or ClusterRoleBinding does not change the credentials `kc-agent` uses. Start `kc-agent` only after switching `KUBECONFIG`/context to dedicated least-privilege credentials and verifying them.
- **Recommended read-only scope:** avoid `resources='*'`, because it includes sensitive objects such as Secrets. Prefer an explicit non-secret resource list and verify access before starting the MCP server:
  ```bash
  kubectl create serviceaccount kc-agent -n default
  kubectl create clusterrole kc-agent-readonly \
    --verb=get,list,watch \
    --resource=pods,services,deployments.apps,replicasets.apps,statefulsets.apps,daemonsets.apps,namespaces,nodes,events,configmaps
  kubectl create clusterrolebinding kc-agent-readonly \
    --clusterrole=kc-agent-readonly \
    --serviceaccount=default:kc-agent
  kubectl auth can-i get secrets --as=system:serviceaccount:default:kc-agent
  kubectl auth can-i list pods --as=system:serviceaccount:default:kc-agent
  ```
- The first `can-i` command must return `no`; the second should return `yes`. Then create or select a kubeconfig that actually authenticates as that ServiceAccount before running `kc-agent`.
- Do not expose `kc-agent` on a public network without authentication.
- Review [SECURITY-AI.md](https://github.com/kubestellar/console/blob/main/docs/security/SECURITY-AI.md) for prompt injection and agent drift mitigations.

## Limitations

- This skill requires an external binary (`kc-agent`) installed separately via Homebrew.
- Do not treat agent output as a substitute for environment-specific validation or expert review.
- Stop and ask for clarification if required permissions or safety boundaries are unclear.

## Links

- [GitHub](https://github.com/kubestellar/console)
- [Website](https://console.kubestellar.io)
- [CLAUDE.md](https://github.com/kubestellar/console/blob/main/CLAUDE.md)
- [AGENTS.md](https://github.com/kubestellar/console/blob/main/AGENTS.md)

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