kube-lint-mcp 0.4.1

MCP server for Kubernetes manifest and Helm chart validation

kube-lint-mcp

mcp-name: io.github.archy-rock3t-cloud/kube-lint-mcp

MCP server that validates Kubernetes manifests and Helm charts with kubectl dry-run before you commit — preventing deployment and GitOps reconciliation failures.

Works with Claude Code, Claude Desktop, and any MCP-compatible client.

How it works

You: "Validate the flux manifests in ./k8s/infrastructure/"

Claude: calls list_kube_contexts → presents list → you confirm "staging"
        calls select_kube_context → flux_dryrun

  FluxCD Dry-Run Validation
  Context: staging
  ================================================
  File: infrastructure/redis.yaml
    Client dry-run: PASS
    Server dry-run: PASS

  File: infrastructure/postgres.yaml
    Client dry-run: PASS
    Server dry-run: FAIL
      Error: namespace "db" not found
  ================================================
  Summary: 1 passed, 1 failed

  DO NOT COMMIT - Fix errors first!

No flags, no CLI args — the AI agent picks the right tool automatically.

Prerequisites

• Python 3.12+
• kubectl configured with cluster access
• helm (for Helm chart validation)
• flux (for Flux operations)

Installation

pip (requires CLI tools installed separately)

pip install kube-lint-mcp

Docker (batteries included)

The Docker image ships with kubectl, helm, flux, and kubeconform — no local installs needed.

docker pull sophotechlabs/kube-lint-mcp:latest
# or: docker pull ghcr.io/sophotechlabs/kube-lint-mcp:latest

Note: If your kubeconfig uses external auth plugins (e.g. gke-gcloud-auth-plugin, aws-iam-authenticator), those binaries are not included in the image. Use the pip install method for those clusters, or embed tokens directly in your kubeconfig.

Configuration

Claude Code (pip)

Add to your project's .mcp.json:

{
  "mcpServers": {
    "kube-lint": {
      "command": "python",
      "args": ["-m", "kube_lint_mcp"]
    }
  }
}

Claude Code (Docker)

{
  "mcpServers": {
    "kube-lint": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-v", "${HOME}:${HOME}:ro",
        "-e", "KUBECONFIG=${HOME}/.kube/config",
        "ghcr.io/sophotechlabs/kube-lint-mcp:latest"
      ]
    }
  }
}

The $HOME:$HOME:ro mount preserves absolute paths that MCP clients send to the server. The read-only flag ensures the container cannot modify your files.

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "kube-lint": {
      "command": "python",
      "args": ["-m", "kube_lint_mcp"]
    }
  }
}

Tools

Tool	Description
select_kube_context	Pick a cluster context (held in memory, no kubeconfig mutation). Call first.
list_kube_contexts	Show available kubectl contexts and which is selected
flux_dryrun	Validate FluxCD YAML with client + server dry-run
kustomize_dryrun	Build and dry-run a Kustomize overlay end-to-end
helm_dryrun	Lint, render, and dry-run a Helm chart end-to-end
flux_check	Verify Flux installation health
flux_status	Show Flux reconciliation status across namespaces
kubeconform_validate	Offline schema validation — no cluster needed

Workflow

1. list_kube_contexts — see available clusters
2. select_kube_context — target a cluster (in-memory only, never mutates kubeconfig)
3. flux_dryrun, kustomize_dryrun, or helm_dryrun — validate before committing
4. Only commit when all checks pass

Safety

The server never mutates your kubeconfig. Context is held in memory and passed via --context flag on every subprocess call. This is a deliberate safety choice for agentic use — the AI cannot accidentally switch your global kubectl context.

Development

pip install -e ".[dev]"
make test    # 126 tests, 100% coverage
make lint    # flake8

Contributing

1. Fork the repo
2. Create a feature branch
3. Make sure make test and make lint pass
4. Open a PR

License

MIT

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