> For clean Markdown of any page, append .md to the page URL. > For a complete documentation index, see https://docs.nvidia.com/nemoclaw/llms.txt. > For full documentation content, see https://docs.nvidia.com/nemoclaw/llms-full.txt. > For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemoclaw/_mcp/server. # NemoClaw Quickstart with OpenClaw > Install NemoClaw, launch a sandbox, and run your first agent prompt. Follow these steps to get started with NemoClaw and your first sandboxed OpenClaw agent. Make sure you have completed reviewing the [Prerequisites](prerequisites) before following this guide. NemoClaw ships user skills for AI coding assistants. Load them when you want your assistant to walk through installation, inference choices, policy approvals, monitoring, or troubleshooting with NemoClaw-specific guidance. Refer to [Agent Skills](../resources/agent-skills). ## 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. NemoClaw creates a fresh OpenClaw instance inside the sandbox during the onboarding process. ```bash curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash ``` The third-party software notice runs before Node.js or the NemoClaw CLI is installed. The piped installer can prompt through your terminal when a TTY is available. In non-TTY contexts, such as CI, an SSH command with piped stdin, or a shell script, pass explicit acceptance to the `bash` side of the pipe: ```bash curl -fsSL https://www.nvidia.com/nemoclaw.sh | NEMOCLAW_ACCEPT_THIRD_PARTY_SOFTWARE=1 bash ``` or pass the installer flag through `bash -s`: ```bash curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash -s -- --yes-i-accept-third-party-software ``` To run both installation and onboarding without prompts, also set non-interactive mode and the provider variables your chosen inference path requires: ```bash curl -fsSL https://www.nvidia.com/nemoclaw.sh | NEMOCLAW_NON_INTERACTIVE=1 NEMOCLAW_ACCEPT_THIRD_PARTY_SOFTWARE=1 bash ``` Do not place `NEMOCLAW_ACCEPT_THIRD_PARTY_SOFTWARE=1` before `curl`. In `NEMOCLAW_ACCEPT_THIRD_PARTY_SOFTWARE=1 curl ... | bash`, the variable applies only to `curl`, so the installer process cannot see the acceptance. 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. On Linux, the installer checks Docker before it installs NemoClaw. If Docker is missing, the installer downloads the official Docker convenience script, asks for `sudo`, installs Docker, and starts the Docker service when systemd is available. If Docker is installed but your current shell cannot use the Docker socket yet, the installer adds your user to the `docker` group when needed and exits with a recovery command. On macOS, the installer uses the Docker-driver OpenShell gateway path with Docker Desktop or Colima. ```bash newgrp docker curl -fsSL https://www.nvidia.com/nemoclaw.sh | bash ``` On DGX Spark, DGX Station, and Windows WSL, an interactive installer offers express install after you accept the third-party software notice. Express install switches onboarding to non-interactive mode, allows `sudo` password prompts for required host changes, and selects the managed local inference path for that platform. Unless `NEMOCLAW_POLICY_TIER` is set, it applies sandbox policy in `suggested` mode with the `balanced` tier by default, using the base sandbox policy plus supported package, model, web-search, and local-inference presets. On DGX Spark, express install uses `my-spark-assistant` as the sandbox name unless `NEMOCLAW_SANDBOX_NAME` is already set. On WSL, express install selects the Windows-host Ollama setup path. Set `NEMOCLAW_NO_EXPRESS=1` to skip the express prompt, or set `NEMOCLAW_PROVIDER` before launching the installer when you want to choose a provider yourself. The installer auto-launches `nemoclaw onboard` when it can locate the freshly-installed binary. If it cannot locate the binary, or if blocking host preflight checks fail, it does not launch the wizard automatically. In that case, the installer prints the relevant diagnostics and a `To finish setup, run:` block with the explicit `nemoclaw onboard` command. 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, asks for an inference provider and model, collects any required credential, then asks for the sandbox name. It prints a review summary before it registers the provider with OpenShell. After you confirm, NemoClaw registers inference, prompts for optional web search and messaging channels, builds and starts the sandbox, sets up OpenClaw, then applies the selected network policy tier and 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 (experimental) 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](../inference/inference-options). 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. 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](../manage-sandboxes/lifecycle#reset-a-stored-credential) to clear and re-enter it. 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. 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. 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. 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`. 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. 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. 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. 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. 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](../inference/use-local-inference). 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 (experimental)**. 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: ```bash 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. * **Local NVIDIA NIM** appears when `NEMOCLAW_EXPERIMENTAL=1` is set and the host has a NIM-capable GPU. NemoClaw pulls and manages a NIM container. * **Local vLLM (already running)** appears whenever NemoClaw detects a vLLM server on `localhost:8000`. No flag is required for the menu entry. NemoClaw auto-detects the loaded model. * **Local vLLM (managed install/start)** appears by default on DGX Spark and DGX Station. Generic Linux NVIDIA GPU hosts require `NEMOCLAW_EXPERIMENTAL=1` or `NEMOCLAW_PROVIDER=install-vllm`. NemoClaw pulls and starts a vLLM container on supported hosts. For setup, refer to [Use a Local Inference Server](../inference/use-local-inference). ### 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: configured for OpenShell gateway registration Web search: disabled Managed tools: none 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, Slack, WeChat, and WhatsApp. Press a channel number to toggle it, then press Enter to continue. If you leave all channels unselected, pressing Enter skips messaging setup. 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-`. WeChat and WhatsApp are experimental. Review [Messaging Channels](../manage-sandboxes/messaging-channels) before enabling them. ### Choose Network Policy Presets After the sandbox image builds and OpenClaw starts inside the sandbox, NemoClaw asks which network policy tier to apply. Web search and messaging selections happen before this point so the sandbox image and the policy suggestions stay aligned. The default **Balanced** tier includes common development presets such as npm, PyPI, Hugging Face, Homebrew, and Brave Search when the selected agent supports web 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 ────────────────────────────────────────────────── NemoClaw is ready Sandbox: my-gpt-claw Model: openai/openai/gpt-5.5 (Other OpenAI-compatible endpoint) Start chatting Browser: http://127.0.0.1:18789/ Terminal: nemoclaw my-gpt-claw connect then run: openclaw tui Authenticated dashboard URL, if needed: nemoclaw my-gpt-claw dashboard-url --quiet Manage later Status: nemoclaw my-gpt-claw status Logs: nemoclaw my-gpt-claw logs --follow Model: nemoclaw inference set --model --provider --sandbox my-gpt-claw Policies: nemoclaw my-gpt-claw policy-add Credentials: nemoclaw credentials reset && nemoclaw onboard ────────────────────────────────────────────────── [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)`. ## 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. If the chosen port becomes occupied after the sandbox build starts, onboarding rolls back the newly-created sandbox and asks you to retry instead of printing an unreachable dashboard URL. The install transcript does not print the gateway token. If the browser requires authentication, use the `dashboard-url --quiet` command to print a complete URL explicitly. ```text nemoclaw my-gpt-claw dashboard-url --quiet ``` Open the dashboard URL in your browser. If the browser asks for authentication, run `nemoclaw my-gpt-claw dashboard-url --quiet` and open the returned URL. Treat the authenticated URL like a password. ### Chat with the Agent from the Terminal Connect to the sandbox and use the OpenClaw CLI. ```bash nemoclaw my-assistant connect # inside the sandbox: openclaw tui ``` ## Next Steps Navigate to the following topics to learn more about NemoClaw. * [NemoClaw Overview](../about/overview) to learn what NemoClaw is and its capabilities. * [Architecture Overview](../about/how-it-works) to understand how NemoClaw works. * [Ecosystem](../about/ecosystem) to understand how OpenClaw, OpenShell, and NemoClaw relate in the wider stack, and when to use NemoClaw versus OpenShell. * [Agent Skills](../resources/agent-skills) to load NemoClaw guidance into an AI coding assistant. Use the following topics to learn how to use NemoClaw. * [Manage NemoClaw sandboxes](../manage-sandboxes/lifecycle) for port forwards, rebuilds, upgrades, and uninstall. * [Inference Options](../inference/inference-options) to use a different model or endpoint. * [Network Policies](../network-policy/approve-network-requests) to manage egress approvals. * [Troubleshooting](../reference/troubleshooting) for common error messages and resolution steps.