> ## Documentation Index
> Fetch the complete documentation index at: https://docs.generalrobotics.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Get started

> Install the GRID CLI, connect your account, and run your first session

Everything in GRID starts from the `grid` CLI — an interactive shell that
onboards robots, starts simulator and robot sessions, and deploys programs.

## 1. Install the CLI

```bash theme={null}
curl -fsSL https://generalrobotics.dev/install.sh | bash
```

Your organization's **GRID admin portal** shows this same command on its
Welcome screen, pre-filled with your cluster:

```bash theme={null}
curl -fsSL https://generalrobotics.dev/install.sh | bash -s -- \
  --cluster-url <your-cluster-url>
```

Prefer the portal variant — it registers your cluster so `login` connects to
the right place immediately. (Windows support is coming soon; use WSL in the
meantime.) On Linux, watching a robot live (`nav view`) needs glibc 2.34 or
newer on x86-64 (Ubuntu 22.04 or later) and 2.30 or newer on ARM64; the rest
of GRID runs on older systems.

The installer verifies a signed binary, installs it to `~/.grid/bin/grid`,
adds it to your `PATH`, and offers the GRID Studio VS Code extension. Open a
new terminal and run:

```bash theme={null}
grid
```

## 2. Log in

Inside the shell, authenticate with your browser:

```text theme={null}
GRID # login
```

Your tokens are stored per cluster; `context use` switches the active cluster
if your organization has more than one (`context list` shows them).

## 3. Get your Cortex API key

Cloud model inference (detection, depth, grasping, VLAs) is authenticated by a
separate runtime key. Generate it in the **admin portal** (the same site that
showed your install command — ask your org admin for its URL if you don't
have it), and paste it when `robot add` asks — the CLI persists it for every
later session.

## 4. Onboard a robot

```text theme={null}
GRID # robot add
```

The wizard walks you through connecting your robot to the GRID network. Once
added, it shows up for everyone in your organization:

```text theme={null}
GRID # robot list
```

## 5. Start working

```text theme={null}
GRID # sim start
```

`sim start` allocates a cloud simulator (it opens a browser workspace with a
live scene). To work against your physical robot, run `skill run --dev` and
choose an online robot. The CLI opens a VS Code workspace in the current folder
with `dev.ipynb` and Python configured. You can start in the notebook or create
a Python file in the editor.

## Where next

* Watch a simulator come alive, no hardware needed: [Your first session](/v2.2/get-started/first-session)
* Write and deploy your first robot program: [Your first skill](/v2.2/get-started/first-skill)
* Every command: the [CLI reference](/v2.2/cli/reference)
* Call cloud models from Python: [grid-cortex-client](/v2.2/python-api/grid-cortex-client/overview)
* The hosted model catalog: [AI models](/v2.2/models/overview)
* Something wrong? `diagnostics` bundles redacted logs for support, and
  `error` recalls the last failure in full.


## Related topics

- [Your first skill](/v2.2/get-started/first-skill.md)
- [Overview](/v2.2/models/overview.md)
- [Your first session](/v2.2/get-started/first-session.md)
- [The Intelligence Grid for Physical AI](/v2.2/introduction.md)
- [GRID Navigator Support](/v2.2/support/grid-navigator.md)


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