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Dstack

A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal…

Install

$npx skills add dstackai/dstack
Claude Code
claude mcp add dstack -- npx skills add dstackai/dstack
Cursor / Claude Desktop (mcp.json)
{
  "mcpServers": {
    "dstack": {
      "command": "npx",
      "args": [
        "skills",
        "add",
        "dstackai/dstack"
      ]
    }
  }
}

Install command taken from the project's README or registry entry. Always review code before running it.

dstack is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters.

It streamlines development, training, and inference, and is compatible with any hardware, open-source tools, and frameworks.

Accelerators

dstack supports NVIDIA, AMD, Google TPU, and Tenstorrent accelerators out of the box.

Latest news ✨

How does it work?

Launch the server

Before using dstack through CLI or API, set up a dstack server. If you already have a running dstack server, you only need to install the CLI.

To orchestrate compute across GPU clouds or Kubernetes clusters, you need to configure backends.

When using dstack with on-prem servers, backend configuration isn’t required. Simply create SSH fleets once the server is up.

The server can be installed on Linux, macOS, and Windows (via WSL 2). It requires Git and OpenSSH.

$ uv tool install "dstack[all]" -U
$ dstack server

Applying ~/.dstack/server/config.yml...

The admin token is "bbae0f28-d3dd-4820-bf61-8f4bb40815da"
The server is running at http://127.0.0.1:3000/

For more details on server configuration options, see the Server deployment guide.

Install the CLI

If the CLI is not installed with the server

Once the server is up, you can access it via the dstack CLI.

The CLI can be installed on Linux, macOS, and Windows. It requires Git and OpenSSH.

$ uv tool install dstack -U

To point the CLI to the dstack server, configure it with the server address, user token, and project name:

$ dstack project add \
    --name main \
    --url http://127.0.0.1:3000 \
    --token bbae0f28-d3dd-4820-bf61-8f4bb40815da

Configuration is updated at ~/.dstack/config.yml

Install agent skills

Install dstack skills to help AI agents use the CLI and edit configuration files.

$ npx skills add dstackai/dstack

AI agents like Claude, Codex, and Cursor can now create and manage fleets and submit workloads on your behalf.

Define configurations

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