Which integrations are available for this server?

Provides tools to refactor, render, and analyze Kubernetes configurations based on Kustomize, including dependency computation and diffing across various overlays and environments.

How do I use Kustomize MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Kustomize MCP Show the diff between the staging and production overlays" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Kustomize MCP

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

asciicast

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_checkpoint: Creates a checkpoint where rendered configuration will be stored.
clear_checkpoint: Clears all checkpoints or a specific checkpoint
render: Renders Kustomize configuration and saves it in a checkpoint
diff_checkpoints: Compares all rendered configuration across two checkpoints
diff_paths: Compares two Kustomize configurations rendered in the same checkpoint
dependencies: Returns dependencies for a Kustomization file

Running the Server

NOTE

This requires access to your local file system, similarly to how thefilesystem 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=/workspace", "ghcr.io/mbrt/kustomize-mcp:latest" ] } } }

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

{ "mcpServers": { "kustomize": { "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" ] } } }