# Nemoclaw User Get Started > Installs NemoClaw, launches a sandbox, and runs the first agent prompt. Use when onboarding, installing, or launching a NemoClaw sandbox for the first time. Trigger keywords - nemoclaw quickstart, install nemoclaw openclaw sandbox, nemohermes quickstart, hermes agent nemoclaw, run hermes openshell sandbox, nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop. - Skill: `promptingcompany/nemoclaw-user-get-started` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add promptingcompany/nemoclaw-user-get-started` - Raw SKILL.md: https://api.skillmd.com/api/skills/promptingcompany/nemoclaw-user-get-started/raw - Safety review: WARNING - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: promptingcompany (https://skillmd.com/u/promptingcompany) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/promptingcompany/nemoclaw-user-get-started --- # NemoClaw Quickstart with OpenClaw Follow these steps to get started with NemoClaw and your first sandboxed OpenClaw agent. > **Note:** Make sure you have completed reviewing the Prerequisites (use the `nemoclaw-user-get-started` skill) before following this guide. ## Step 1: Install NemoClaw and Onboard OpenClaw Agent Download and run the installer script. The script installs Node.js if it is not already present, then runs the guided onboard wizard to create a sandbox, configure inference, and apply security policies. > **Note:** NemoClaw creates a fresh OpenClaw instance inside the sandbox during the onboarding process. ```bash curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash ``` The piped installer prompts through your terminal. In headless scripts or CI, pass explicit acceptance to the `bash` side of the pipe: ```console $ curl -fsSL https://www.nvidia.com/nemoclaw.sh | NEMOCLAW_NON_INTERACTIVE=1 NEMOCLAW_ACCEPT_THIRD_PARTY_SOFTWARE=1 bash ``` If you use nvm or fnm to manage Node.js, the installer might not update your current shell's PATH. If `nemoclaw` is not found after install, run `source ~/.bashrc` (or `source ~/.zshrc` for zsh) or open a new terminal. > **Note:** The onboard flow builds the sandbox image with `NEMOCLAW_DISABLE_DEVICE_AUTH=1` so the dashboard is immediately usable during setup. > This is a build-time setting baked into the sandbox image, not a runtime knob. > If you export `NEMOCLAW_DISABLE_DEVICE_AUTH` after onboarding finishes, it has no effect on an existing sandbox. ### Respond to the Onboard Wizard After the installer launches `nemoclaw onboard`, the wizard runs preflight checks, starts or reuses the OpenShell gateway, and asks for an inference provider, sandbox name, optional web search, optional messaging channels, and network policy presets. At any prompt, press Enter to accept the default shown in `[brackets]`, type `back` to return to the previous prompt, or type `exit` to quit. If existing sandbox sessions are running, the installer warns before onboarding because the setup can rebuild or upgrade sandboxes after the new sandbox launches. The inference provider prompt presents a numbered list. ```text 1) NVIDIA Endpoints 2) OpenAI 3) Other OpenAI-compatible endpoint 4) Anthropic 5) Other Anthropic-compatible endpoint 6) Google Gemini 7) Local Ollama (localhost:11434) 8) Model Router (complexity-based routing) Choose [1]: ``` Pick the option that matches where you want inference traffic to go, then expand the matching helper below for the follow-up prompts and the API key environment variable to set. For the full list of providers and validation behavior, refer to Inference Options (use the `nemoclaw-user-configure-inference` skill). Local Ollama appears when NemoClaw detects a usable local Ollama path or can offer an install or start action for your platform. The Model Router option appears when the blueprint router profile is enabled. > **Tip:** Export the API key before launching the installer so the wizard does not have to ask for it. > For example, run `export NVIDIA_API_KEY=` before `curl ... | bash`. > If you entered a key incorrectly, refer to Reset a Stored Credential (use the `nemoclaw-user-manage-sandboxes` skill) to clear and re-enter it. :::{dropdown} Option 1: NVIDIA Endpoints :icon: server Routes inference to models hosted on [build.nvidia.com](https://build.nvidia.com). Use `NVIDIA_API_KEY` for the API key. Get one from the [NVIDIA build API keys page](https://build.nvidia.com/settings/api-keys). Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, press Enter (or type `1`) to select **NVIDIA Endpoints**. 2. At the `NVIDIA_API_KEY:` prompt, paste your key if it is not already exported. 3. At the `Choose model [1]:` prompt, pick a curated model from the list (for example, `Nemotron 3 Super 120B`, `GLM-5`, `MiniMax M2.7`, `GPT-OSS 120B`, or `DeepSeek V4 Pro`), or pick `Other...` to enter any model ID from the [NVIDIA Endpoints catalog](https://build.nvidia.com). NemoClaw validates the model against the catalog API before creating the sandbox. > **Tip:** Use this option for Nemotron and other models hosted on `build.nvidia.com`. If you run NVIDIA Nemotron from a self-hosted NIM, an enterprise gateway, or any other endpoint, choose **Option 3** instead, since all Nemotron models expose OpenAI-compatible APIs. ::: :::{dropdown} Option 2: OpenAI :icon: server Routes inference to the OpenAI API at `https://api.openai.com/v1`. Use `OPENAI_API_KEY` for the API key. Get one from the [OpenAI API keys page](https://platform.openai.com/api-keys). Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, type `2` to select **OpenAI**. 2. At the `OPENAI_API_KEY:` prompt, paste your key if it is not already exported. 3. At the `Choose model [1]:` prompt, pick a curated model (for example, `gpt-5.4`, `gpt-5.4-mini`, `gpt-5.4-nano`, or `gpt-5.4-pro-2026-03-05`), or pick **Other...** to enter any OpenAI model ID. ::: :::{dropdown} Option 3: Other OpenAI-Compatible Endpoint :icon: link-external Routes inference to any server that implements `/v1/chat/completions`, including OpenRouter, LocalAI, llama.cpp, vLLM behind a proxy, and any compatible gateway. Use `COMPATIBLE_API_KEY` for the API key. Set it to whatever credential your endpoint expects. If your endpoint does not require auth, use any non-empty placeholder. Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, type `3` to select **Other OpenAI-compatible endpoint**. 2. At the `OpenAI-compatible base URL` prompt, enter the provider's base URL. Find the exact value in your provider's API documentation. NemoClaw appends `/v1` automatically, so leave that suffix off. 3. At the `COMPATIBLE_API_KEY:` prompt, paste your key if it is not already exported. 4. At the `Other OpenAI-compatible endpoint model []:` prompt, enter the model ID exactly as it appears in your provider's model catalog. For example, when you use NVIDIA's OpenAI-compatible inference endpoint, enter `https://inference-api.nvidia.com` as the base URL and the model ID your endpoint exposes, such as `openai/openai/gpt-5.5`. NemoClaw sends a real inference request to validate the endpoint and model. If the endpoint does not return the streaming events OpenClaw needs from the Responses API, NemoClaw falls back to the chat completions API and configures OpenClaw to use `openai-completions`. > **Tip:** NVIDIA Nemotron models expose OpenAI-compatible APIs, so this option is the right choice for any Nemotron deployment that does not live on `build.nvidia.com`. Common examples include a self-hosted NIM container, an enterprise NVIDIA AI Enterprise gateway, or a vLLM/SGLang server running Nemotron weights. Point the base URL at your endpoint and enter the Nemotron model ID exactly as your server reports it. ::: :::{dropdown} Option 4: Anthropic :icon: server Routes inference to the Anthropic Messages API at `https://api.anthropic.com`. Use `ANTHROPIC_API_KEY` for the API key. Get one from the [Anthropic console keys page](https://console.anthropic.com/settings/keys). Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, type `4` to select **Anthropic**. 2. At the `ANTHROPIC_API_KEY:` prompt, paste your key if it is not already exported. 3. At the `Choose model [1]:` prompt, pick a curated model (for example, `claude-sonnet-4-6`, `claude-haiku-4-5`, or `claude-opus-4-6`), or pick **Other...** to enter any Claude model ID. ::: :::{dropdown} Option 5: Other Anthropic-Compatible Endpoint :icon: link-external Routes inference to any server that implements the Anthropic Messages API at `/v1/messages`, including Claude proxies, Bedrock-compatible gateways, and self-hosted Anthropic-compatible servers. Use `COMPATIBLE_ANTHROPIC_API_KEY` for the API key. Set it to whatever credential your endpoint expects. Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, type `5` to select **Other Anthropic-compatible endpoint**. 2. At the `Anthropic-compatible base URL` prompt, enter the proxy or gateway's base URL from its documentation. 3. At the `COMPATIBLE_ANTHROPIC_API_KEY:` prompt, paste your key if it is not already exported. 4. At the `Other Anthropic-compatible endpoint model []:` prompt, enter the model ID exactly as it appears in your gateway's model catalog. ::: :::{dropdown} Option 6: Google Gemini :icon: server Routes inference to Google's OpenAI-compatible Gemini endpoint at `https://generativelanguage.googleapis.com/v1beta/openai/`. Use `GEMINI_API_KEY` for the API key. Get one from [Google AI Studio API keys](https://aistudio.google.com/app/apikey). Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, type `6` to select **Google Gemini**. 2. At the `GEMINI_API_KEY:` prompt, paste your key if it is not already exported. 3. At the `Choose model [5]:` prompt, pick a curated model (for example, `gemini-3.1-pro-preview`, `gemini-3.1-flash-lite-preview`, `gemini-3-flash-preview`, `gemini-2.5-pro`, `gemini-2.5-flash`, or `gemini-2.5-flash-lite`), or pick **Other...** to enter any Gemini model ID. ::: :::{dropdown} Option 7: Local Ollama :icon: cpu Routes inference to a local Ollama instance. Depending on your platform, the wizard can use an existing daemon, start an installed daemon, or offer an install action. No API key is required. On non-WSL hosts, NemoClaw generates a token and starts an authenticated proxy so containers can reach Ollama without exposing the daemon directly to your network. On WSL, NemoClaw can also use Ollama on the Windows host through `host.docker.internal`. Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, type `7` to select **Local Ollama**. 2. At the `Choose model [1]:` prompt, pick from **Ollama models** if any are already installed. If none are installed, pick a **starter model** to pull and load now, or pick **Other...** to enter any Ollama model ID. For setup details, including GPU recommendations and starter model choices, refer to Use a Local Inference Server (use the `nemoclaw-user-configure-inference` skill). ::: :::{dropdown} Option 8: Model Router :icon: git-compare Starts a host-side model router and routes sandbox inference through OpenShell to that router. The router chooses from the model pool in `nemoclaw-blueprint/router/pool-config.yaml` for each request. Use `NVIDIA_API_KEY` for the model pool credentials. Respond to the wizard as follows. 1. At the `Choose [1]:` prompt, type `8` to select **Model Router (complexity-based routing)**. 2. At the `NVIDIA_API_KEY:` prompt, paste your key if it is not already exported. 3. Review the configuration summary and continue with the sandbox build. For scripted setup, set: ```console $ NEMOCLAW_PROVIDER=routed NVIDIA_API_KEY= nemoclaw onboard --non-interactive ``` The router listens on the host at port `4000`. The sandbox still calls `https://inference.local/v1`, so do not point in-sandbox tools at the host router port directly. ::: :::{dropdown} Experimental: Local NIM and Local vLLM :icon: beaker These options appear when `NEMOCLAW_EXPERIMENTAL=1` is set and the prerequisites are met. - **Local NVIDIA NIM** requires a NIM-capable GPU. NemoClaw pulls and manages a NIM container. - **Local vLLM** uses a vLLM server already running on `localhost:8000`, or installs and starts a managed vLLM container on supported DGX Spark, DGX Station, and Linux NVIDIA GPU hosts. NemoClaw auto-detects the loaded model. For setup, refer to Use a Local Inference Server (use the `nemoclaw-user-configure-inference` skill). ::: ### Review the Configuration Before the Sandbox Build After you enter the sandbox name, the wizard prints a review summary and asks for final confirmation before registering the provider, prompting for optional integrations, and building the sandbox image. For example, if you picked an OpenAI-compatible endpoint, the summary looks like the following: ```text ────────────────────────────────────────────────── Review configuration ────────────────────────────────────────────────── Provider: compatible-endpoint Model: openai/openai/gpt-5.5 API key: COMPATIBLE_API_KEY (staged for OpenShell gateway registration) Web search: disabled Messaging: none Sandbox name: my-gpt-claw Note: Sandbox build typically takes 5–15 minutes on this host. ────────────────────────────────────────────────── Web search and messaging channels will be prompted next. Apply this configuration? [Y/n]: ``` The default is `Y`, so you can press Enter once to continue. Answer `n` to abort cleanly, fix the entries, and re-run `nemoclaw onboard`. Non-interactive runs (`NEMOCLAW_NON_INTERACTIVE=1`) print the summary for log clarity but skip the prompt. ### Configure Web Search and Messaging After you confirm the summary, NemoClaw registers the selected provider with the OpenShell gateway and sets the `inference.local` route. The wizard then asks whether to enable Brave Web Search. If you enable it, enter a Brave Search API key when prompted. The wizard also offers messaging channels such as Telegram, Discord, and Slack. Press a channel number to toggle it, then press Enter to continue. If you select a channel, NemoClaw validates the token format before it bakes the channel configuration into the sandbox. For example, Slack bot tokens must start with `xoxb-`. ### Choose Network Policy Presets After the sandbox image builds and OpenClaw starts inside the sandbox, NemoClaw asks which network policy tier to apply. The default **Balanced** tier includes common development presets such as npm, PyPI, Hugging Face, Homebrew, and Brave Search. Use the arrow keys or `j` and `k` to move, Space to select, and Enter to confirm. The preset selector lets you include more destinations, such as GitHub, Jira, Slack, Telegram, or local inference. Press `r` to toggle a selected preset between read-only and read-write when the preset supports both modes. When the install completes, a summary confirms the running environment. Before printing the summary, NemoClaw verifies that the sandbox gateway and dashboard port forward are reachable. Inference route and messaging bridge checks are reported as warnings when they need more time or additional configuration. The `Model` and provider line reflects the inference option you picked during onboarding. The example below shows the result if you picked an OpenAI-compatible endpoint during onboarding. ```text ────────────────────────────────────────────────── Sandbox my-gpt-claw (Landlock + seccomp + netns) Model openai/openai/gpt-5.5 (Other OpenAI-compatible endpoint) ────────────────────────────────────────────────── Run: nemoclaw my-gpt-claw connect Status: nemoclaw my-gpt-claw status Logs: nemoclaw my-gpt-claw logs --follow ────────────────────────────────────────────────── [INFO] === Installation complete === ``` If you picked a different option, the `Model` line shows that provider's model and label instead. For example, you might see `gpt-5.4 (OpenAI)`, `claude-sonnet-4-6 (Anthropic)`, `gemini-2.5-flash (Google Gemini)`, `llama3.1:8b (Local Ollama)`, `nvidia-routed (Model Router)`, or ` (Other OpenAI-compatible endpoint)`. ## Step 2: Run Your First Agent Prompt You can chat with the agent from the terminal or the browser. ### Open the OpenClaw UI in a Browser to Chat with the Agent The onboard wizard starts a background port forward to the sandbox dashboard, then prints the dashboard URL in the install summary. The default host port is `18789`. If that port is already taken, NemoClaw uses the next free dashboard port, such as `18790`, and prints that port in the final URL. The gateway token is redacted from displayed output; retrieve it explicitly when the browser asks for authentication. ```text ────────────────────────────────────────────────── OpenClaw UI (auth token redacted from displayed URLs) Port 18790 must be forwarded before opening these URLs. Dashboard: http://127.0.0.1:18790/ Token: nemoclaw my-gpt-claw gateway-token --quiet append #token= locally if the browser asks for auth. ────────────────────────────────────────────────── ``` Open the dashboard URL in your browser. If the browser asks for authentication, run the printed `gateway-token --quiet` command and append `#token=` locally. Treat the token like a password. ### Chat with the Agent from the Terminal Connect to the sandbox and use the OpenClaw CLI. ```bash nemoclaw my-assistant connect ``` In the sandbox shell, send a single message and print the response. ```bash openclaw agent --agent main --local -m "hello" --session-id test ``` ## References - **Load [references/quickstart-hermes.md](references/quickstart-hermes.md)** when users ask for Hermes setup, NemoHermes onboarding, or running Hermes inside OpenShell. Installs NemoClaw, selects the Hermes agent, and launches a sandboxed Hermes API endpoint. - **Load [references/prerequisites.md](references/prerequisites.md)** when verifying prerequisites before installation. Lists the hardware, software, and container runtime requirements for running NemoClaw. - **Load [references/windows-preparation.md](references/windows-preparation.md)** when preparing a Windows machine for NemoClaw, enabling WSL 2, configuring Docker Desktop for Windows, or troubleshooting a Windows-specific install error. Covers Windows-only preparation steps required before the Quickstart. ## Related Skills - `nemoclaw-user-manage-sandboxes` — Manage NemoClaw sandboxes (use the `nemoclaw-user-manage-sandboxes` skill) for port forwards, rebuilds, upgrades, and uninstall - `nemoclaw-user-configure-inference` — Switch inference providers (use the `nemoclaw-user-configure-inference` skill) to use a different model or endpoint - `nemoclaw-user-manage-policy` — Approve or deny network requests (use the `nemoclaw-user-manage-policy` skill) when the agent tries to reach external hosts - `nemoclaw-user-deploy-remote` — Deploy to a remote GPU instance (use the `nemoclaw-user-deploy-remote` skill) for always-on operation - `nemoclaw-user-monitor-sandbox` — Monitor sandbox activity (use the `nemoclaw-user-monitor-sandbox` skill) through the OpenShell TUI - `nemoclaw-user-reference` — Consult the troubleshooting guide (use the `nemoclaw-user-reference` skill) for common error messages and resolution steps