# Nemoclaw User Get Started > Lists the hardware, software, and container runtime requirements for running NemoClaw. Use when verifying prerequisites before installation. Trigger keywords - nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw quickstart, install nemoclaw openclaw sandbox, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop. - Skill: `composio-community/nemoclaw-user-get-started` (Agent Skill, multi-file: 3 files) - Install (CLI): `npx skillmds@latest add composio-community/nemoclaw-user-get-started` - Raw SKILL.md: https://api.skillmd.com/api/skills/composio-community/nemoclaw-user-get-started/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: composio-community (https://skillmd.com/u/composio-community) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/composio-community/nemoclaw-user-get-started --- # NemoClaw Prerequisites ## Gotchas - Ollama binds to `0.0.0.0` so the sandbox can reach it through Docker. 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 ``` 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 walks you through a sandbox name, an inference provider, and a network policy preset. 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. 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 (only shown when Ollama is detected on the host) 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). > **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](#reset-a-stored-credential) 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**, **Kimi K2.5**, **GLM-5.1**, **MiniMax M2.5**, or **GPT-OSS 120B**), 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, `openai/gpt-5.4` on OpenRouter). NemoClaw sends a real inference request to validate the endpoint and model. NemoClaw forces the chat completions API for compatible endpoints because many backends advertise `/v1/responses` but mishandle the `developer` role used by the Responses API. > **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 on `localhost:11434`. This option only appears when Ollama is installed or running on the host. No API key is required. NemoClaw generates a token and starts an authenticated proxy so containers can reach Ollama without exposing it to your network. 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). > **Warning:** Ollama binds to `0.0.0.0` so the sandbox can reach it through Docker. On public WiFi, any device on the same network can send prompts to your GPU through the Ollama API. Refer to CNVD-2025-04094 and CVE-2024-37032. ::: :::{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** requires a vLLM server already running on `localhost:8000`. 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 starting the destructive sandbox image build. For example, if you picked NVIDIA Endpoints, the summary looks like the following: ```text ────────────────────────────────────────────────── Review configuration ────────────────────────────────────────────────── Provider: nvidia-api Model: nvidia/nemotron-3-super-120b-a12b API key: NVIDIA_API_KEY (stored in ~/.nemoclaw/credentials.json) Web search: disabled Messaging: none Sandbox name: my-assistant ────────────────────────────────────────────────── 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. When the install completes, a summary confirms the running environment. The `Model` and provider line reflects the inference option you picked during onboarding. The example below shows the result if you picked NVIDIA Endpoints during onboarding. ```text ────────────────────────────────────────────────── Sandbox my-assistant (Landlock + seccomp + netns) Model nvidia/nemotron-3-super-120b-a12b (NVIDIA Endpoints) ────────────────────────────────────────────────── Run: nemoclaw my-assistant connect Status: nemoclaw my-assistant status Logs: nemoclaw my-assistant 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)`, or ` (Other OpenAI-compatible endpoint)`. ## Step 2: Open the OpenClaw UI in a Browser The onboard wizard automatically starts an SSH port forward from your host's `127.0.0.1:18789` to the sandbox dashboard, then prints a tokenized URL in the install summary. ```text ────────────────────────────────────────────────── OpenClaw UI (tokenized URL; treat it like a password; save it now - it will not be printed again) Port 18789 must be forwarded before opening these URLs. Dashboard: http://127.0.0.1:18789/#token= ────────────────────────────────────────────────── ``` Open that URL in your browser. The `#token=` fragment authenticates the browser to the sandbox gateway, so save the URL securely and treat it like a password. NemoClaw prints the token only once. ### Restart the Port Forward If the forward stopped (for example, after a reboot) or you opened a new terminal and the URL no longer responds, restart it manually. ```bash openshell forward start --background 18789 my-assistant ``` To list active forwards across all sandboxes, run the following command. ```bash openshell forward list ``` ### Run Multiple Sandboxes Each sandbox needs its own dashboard port, since `openshell forward` refuses to bind a port that another sandbox is already using. Override the port with `CHAT_UI_URL` at onboard time — the dashboard port is derived automatically. ```console $ nemoclaw onboard # first sandbox uses 18789 $ CHAT_UI_URL=http://127.0.0.1:19000 nemoclaw onboard # second sandbox uses 19000 ``` You can also use `NEMOCLAW_DASHBOARD_PORT` directly if you prefer: ```console $ NEMOCLAW_DASHBOARD_PORT=19000 nemoclaw onboard ``` For full details on port conflicts and overrides, refer to Port already in use (use the `nemoclaw-user-reference` skill). ### Open the UI from a Remote Host If NemoClaw is running on a remote GPU instance and you want to open the UI from a laptop, refer to Remote Dashboard Access (use the `nemoclaw-user-deploy-remote` skill). Set `CHAT_UI_URL` to the origin the browser uses before running onboard, so the gateway's CORS allowlist accepts the remote browser. ## Step 3: Chat with the Agent from the Terminal If you prefer a terminal-based chat, connect to the sandbox and use the OpenClaw CLI. ```bash nemoclaw my-assistant connect ``` In the sandbox shell, open the OpenClaw terminal UI and start a chat. ```bash openclaw tui ``` Alternatively, send a single message and print the response. ```bash openclaw agent --agent main --local -m "hello" --session-id test ``` ## Step 4: Reconfigure or Recover Recover from a misconfigured sandbox without re-running the full onboard wizard or destroying workspace state. ### Change Inference Model or API Change the active model or provider at runtime without rebuilding the sandbox: ```console $ openshell inference set -g nemoclaw --model --provider ``` Refer to Switch inference providers (use the `nemoclaw-user-configure-inference` skill) for provider-specific model IDs and API compatibility notes. ### Reset a Stored Credential If an API key was entered incorrectly during onboarding, clear the stored value and re-enter it on the next onboard run: ```console $ nemoclaw credentials list # see which keys are stored $ nemoclaw credentials reset # clear a single key, for example NVIDIA_API_KEY $ nemoclaw onboard # re-run to re-enter the cleared key ``` The credentials command is documented in full at `nemoclaw credentials reset ` (use the `nemoclaw-user-reference` skill). ### Rebuild a Sandbox While Preserving Workspace State If you changed the underlying Dockerfile, upgraded OpenClaw, or want to pick up a new base image without losing your sandbox's workspace files, use `rebuild` instead of destroying and recreating: ```console $ nemoclaw rebuild ``` Rebuild preserves the mounted workspace and registered policies while recreating the container. Refer to `nemoclaw rebuild` (use the `nemoclaw-user-reference` skill) for flag details. ### Add a Network Preset After Onboarding Apply an additional preset (for example, Telegram or GitHub) to a running sandbox without re-onboarding: ```console $ nemoclaw policy-add ``` Refer to `nemoclaw policy-add` (use the `nemoclaw-user-reference` skill) for usage details and flags. ## Step 5: Uninstall To remove NemoClaw and all resources created during setup, run the CLI's built-in uninstall command: ```bash nemoclaw uninstall ``` | Flag | Effect | |--------------------|-----------------------------------------------------| | `--yes` | Skip the confirmation prompt. | | `--keep-openshell` | Leave the `openshell` binary installed. | | `--delete-models` | Also remove NemoClaw-pulled Ollama models. | `nemoclaw uninstall` runs the version-pinned `uninstall.sh` that shipped with your installed CLI, so it does not fetch anything over the network at uninstall time. If the `nemoclaw` CLI is missing or broken, fall back to the hosted script: ```bash curl -fsSL https://raw.githubusercontent.com/NVIDIA/NemoClaw/refs/heads/main/uninstall.sh | bash ``` For a full comparison of the two forms — what they fetch, what they trust, and when to prefer each — see `nemoclaw uninstall` vs. the hosted `uninstall.sh` (use the `nemoclaw-user-reference` skill). ## References - **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-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