Kustomize MCP

An MCP server that helps to refactor Kubernetes configuration based on Kustomize.

Why? Because Kustomize manifests depend on each other in non-obvious ways, it's hard for a model to understand how a config change may impact multiple environments. This MCP server gives them extra tools to make this safer:

• Compute dependencies of a manifest
• Render the end result of Kustomize overlays
• Provide full and summarized diffs between overlays across directories and checkpoints.

Available Tools

• create_kustomize_checkpoint: Creates a checkpoint where rendered configuration will be stored.
• clear_kustomize_checkpoint: Clears all checkpoints or a specific checkpoint
• render_kustomize: Renders Kustomize configuration and saves it in a checkpoint
• diff_kustomize_checkpoints: Compares all rendered configuration across two checkpoints
• diff_kustomize_paths: Compares two Kustomize configurations rendered in the same checkpoint
• kustomization_dependencies: Returns dependencies for a Kustomization file

Running the Server

Note

This requires access to your local file system, similarly to how the filesystem MCP Server works.

Using Docker

Run the server in a container (using the pre-built image):

docker run -i --rm -v "$(pwd):/workspace" ghcr.io/mbrt/kustomize-mcp:latest

The Docker image includes:

• Python 3.13 with all project dependencies
• kustomize (latest stable)
• helm (latest stable)
• git

Mount your Kustomize configurations to the /workspace directory in the container to work with them.

If you want to rebuild the image from source:

docker build -t my-kustomize-mcp:latest .

And use that image instead of ghcr.io/mbrt/kustomize-mcp.

Using UV (Local Development)

Start the MCP server:

uv run server.py

The server will start by using the STDIO transport.

Usage with MCP clients

To integrate with VS Code, add the configuration to your user-level MCP configuration file. Open the Command Palette (Ctrl + Shift + P) and run MCP: Open User Configuration. This will open your user mcp.json file where you can add the server configuration.

{
  "servers": {
    "kustomize": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--mount", "type=bind,src=${workspaceFolder},dst=/projects/workspace",
        "mcp/filesystem",
        "/projects"
      ]
    }
  }
}

To integrate with Claude Code, add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "kustomizeRefactor": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-a", "stdin",
        "-a", "stdout",
        "-v", "<PROJECT_DIR>:/workspace",
        "ghcr.io/mbrt/kustomize-mcp:latest"
      ]
    }
  }
}

Replace <PROJECT_DIR> with the root directory of your project.

To integrate with Gemini CLI, edit .gemini/settings.json:

{
  "mcpServers": {
    "kustomize": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-a", "stdin",
        "-a", "stdout",
        "-v", "${PWD}:/workspace",
        "ghcr.io/mbrt/kustomize-mcp:latest"
      ]
    }
  }
}

Testing the Server

Run unit tests:

pytest

After running the server on one shell, use the dev tool to verify the server is working:

uv run mcp dev ./server.py