> ## Documentation Index
> Fetch the complete documentation index at: https://dimensional-cc-refactor-keyboard-teleop.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Install DimOS, run a replay or simulation, then explore CLI and MCP. No hardware required.

In this quickstart, you will be able to replay a Unitree Go2 office navigation session with no hardware, switch to simulation or a live robot.

If you use coding agents (OpenClaw, Claude Code or similar), point them at [`AGENTS.md`](https://github.com/dimensionalOS/dimos/blob/main/AGENTS.md).

## System requirements

| Component      | Minimum                      | Recommended             |
| -------------- | ---------------------------- | ----------------------- |
| OS             | Ubuntu 22.04, macOS 12.6+    | Ubuntu 24.04            |
| Python         | 3.12                         | Latest                  |
| RAM            | 16 GB                        | 32 GB+                  |
| Disk           | 10 GB SSD                    | 25 GB+ SSD              |
| CPU            | 8-core Intel / AMD           | 12+ cores               |
| GPU (optional) | NVIDIA RTX 3000+ (8 GB VRAM) | RTX 4070+ (12 GB+ VRAM) |

> GPU is required only for perception, VLMs, and AI features. Optional for basic robot control.

## Interactive install

```bash theme={null}
curl -fsSL https://raw.githubusercontent.com/dimensionalOS/dimos/main/scripts/install.sh | bash
```

## Manual system install

If you prefer to install system dependencies yourself, follow the guide for your OS:

| OS Guide                                                                                                                                   | Notes                                  |
| ------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------- |
| <Icon icon="ubuntu" iconType="brands" size={18} />  [Ubuntu](https://github.com/dimensionalOS/dimos/blob/main/docs/installation/ubuntu.md) | Primary tested path                    |
| <Icon icon="snowflake" iconType="solid" size={18} /> [Nix](https://github.com/dimensionalOS/dimos/blob/main/docs/installation/nix.md)      | Flakes and dev shell                   |
| <Icon icon="apple" iconType="brands" size={18} /> [macOS](https://github.com/dimensionalOS/dimos/blob/main/docs/installation/osx.md)       | Homebrew-based; less mature than Linux |

## Python environment

DimOS targets Python 3.12. The examples use [`uv`](https://docs.astral.sh/uv/); plain `python -m venv` and `pip` work too.

```bash theme={null}
uv venv --python "3.12"
source .venv/bin/activate   # Windows: .venv\Scripts\activate
```

## Install DimOS

```bash theme={null}
uv pip install 'dimos[base,unitree]'
```

Extras keep installs lean: `base` is runtime, modules, transports, and CLI; `unitree` adds WebRTC and skills for Go2 / G1 (real or replayed).

### Replay a recorded session (no hardware)

On first run, the Rerun window may stay black briefly while roughly **75 MB** of data downloads from LFS.

```bash theme={null}
dimos --replay run unitree-go2
```

### Simulation (MuJoCo)

```bash theme={null}
uv pip install 'dimos[base,unitree,sim]'
dimos --simulation run unitree-go2
dimos --simulation run unitree-g1-sim   # humanoid
```

### Real robot (example: Unitree Go2 over WebRTC)

```bash theme={null}
export ROBOT_IP=<YOUR_ROBOT_IP>
dimos run unitree-go2
```

Do not skip the platform guide - latency, time sync, and safety habits matter: [Unitree Go2](https://github.com/dimensionalOS/dimos/blob/main/docs/platforms/quadruped/go2/index.md).

## Featured runfiles

| Command                                                           | What it does                                                      |
| ----------------------------------------------------------------- | ----------------------------------------------------------------- |
| `dimos --replay run unitree-go2`                                  | Quadruped navigation replay - SLAM, costmap, A-star planning      |
| `dimos --replay --replay-db go2_bigoffice run unitree-go2-memory` | Quadruped temporal memory replay                                  |
| `dimos --simulation run unitree-go2-agentic`                      | Quadruped agentic + MCP server in simulation                      |
| `dimos --simulation run unitree-g1-sim`                           | Humanoid in MuJoCo simulation                                     |
| `dimos --replay run drone-basic`                                  | Drone video + telemetry replay                                    |
| `dimos --replay run drone-agentic`                                | Drone + LLM agent with flight skills (replay)                     |
| `dimos run demo-camera`                                           | Webcam demo - no hardware needed                                  |
| `dimos run keyboard-teleop-xarm7`                                 | Keyboard teleop with mock xArm7 (`dimos[manipulation]` extra)     |
| `dimos --simulation run unitree-go2-agentic-ollama`               | Quadruped agentic with local LLM (Ollama running, `ollama serve`) |

Blueprint reference: [Blueprints](https://github.com/dimensionalOS/dimos/blob/main/docs/usage/blueprints.md).

## Agent CLI and MCP

The `dimos` CLI runs blueprints, inspects state, talks to agents, and invokes skills via MCP.

```bash theme={null}
dimos run unitree-go2-agentic --daemon   # background
dimos status
dimos log -f
dimos agent-send "explore the room"
dimos mcp list-tools
dimos mcp call relative_move --arg forward=0.5
dimos stop
```

Full reference: [CLI](https://github.com/dimensionalOS/dimos/blob/main/docs/usage/cli.md).

## What next?

<CardGroup cols={2}>
  <Card title="Add an LLM agent" icon="robot">
    Natural language control and MCP-exposed skills.
  </Card>

  <Card title="Pick your platform" icon="microchip">
    Hardware support matrix and bring-up guides.
  </Card>

  <Card title="Core concepts" icon="diagram-project">
    Modules, streams, and blueprints behind every workflow.
  </Card>

  <Card title="Capabilities" icon="bolt">
    Navigation, perception, spatial memory, and manipulation.
  </Card>
</CardGroup>