What prerequisites are needed?
Python 3.8+, Helm CLI installed, and optionally Docker for containerized deployment.
@jeff-nasseri
基本信息
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.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"helm": {
"command": "docker",
"args": [
"build",
"-t",
"mcp-helm",
"."
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
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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