What prerequisites are needed?
Python 3.8+, Helm CLI installed, and optionally Docker for containerized deployment.
@jeff-nasseri
Basic information
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.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"helm": {
"command": "docker",
"args": [
"build",
"-t",
"mcp-helm",
"."
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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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