What prerequisites are needed?
Python 3.8+, Helm CLI installed, and optionally Docker for containerized deployment.
@jeff-nasseri
基本情報
Helm MCP provides a bridge between AI assistants and the Helm package manager for Kubernetes. It allows AI assistants to interact with Helm through natural language requests, executing commands like installing charts, managing repositories, and more.
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"helm": {
"command": "docker",
"args": [
"build",
"-t",
"mcp-helm",
"."
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
Helm Chart Cli is an MCP server that bridges AI assistants with the Helm package manager for Kubernetes. It allows AI assistants to interact with Helm through natural language requests, executing commands like installing charts and managing repositories.
Requires Python 3.8+ and the Helm CLI installed. Deploy via Docker (build from the repo) or manually: clone the repository, create a virtual environment, install dependencies with uv, and run mcp-server-helm. The server exposes dozens of tools mapped to standard Helm commands.
Python 3.8+, Helm CLI installed, and optionally Docker for containerized deployment.
Clone the repository, then either build the Docker image (`docker build -t mcp-helm`) or install manually with `uv` and run `mcp-server-helm`.
Over 30 tools covering chart creation, dependency management, release management, repository management, registry operations, and release information.
Yes, via `helm_registry_login` and `helm_registry_logout` with username/password credentials.
The README does not specify any transport or authentication for the MCP server; it runs as a direct server process (e.g., `mcp-server-helm`).

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