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nvidia-nemoclaw

NVIDIA NemoClaw plugin for secure sandboxed installation and orchestration of OpenClaw always-on AI assistants via OpenShell

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Skill instructions

Rendered from the published SKILL.md, 441 lines.

NVIDIA NemoClaw

Skill by ara.so — Daily 2026 Skills collection.

NVIDIA NemoClaw is an open-source TypeScript CLI plugin that simplifies running OpenClaw always-on AI assistants securely. It installs and orchestrates the NVIDIA OpenShell runtime, creates policy-enforced sandboxes, and routes all inference through NVIDIA cloud (Nemotron models). Network egress, filesystem access, syscalls, and model API calls are all governed by declarative policy.

Status: Alpha — interfaces and APIs may change without notice.


Installation

Prerequisites

  • Linux Ubuntu 22.04 LTS or later
  • Node.js 20+ and npm 10+ (Node.js 22 recommended)
  • Docker installed and running
  • NVIDIA OpenShell installed

One-Line Installer

curl -fsSL https://nvidia.com/nemoclaw.sh | bash

This installs Node.js (if absent), runs the guided onboard wizard, creates a sandbox, configures inference, and applies security policies.

Manual Install (from source)

git clone https://github.com/NVIDIA/NemoClaw.git
cd NemoClaw
npm install
npm run build
npm link  # makes `nemoclaw` available globally

Environment Variables

# Required: NVIDIA cloud API key for Nemotron inference
export NVIDIA_API_KEY="nvapi-xxxxxxxxxxxx"

# Optional: override default model
export NEMOCLAW_MODEL="nvidia/nemotron-3-super-120b-a12b"

# Optional: custom sandbox data directory
export NEMOCLAW_SANDBOX_DIR="/var/nemoclaw/sandboxes"

Get an API key at build.nvidia.com.


Quick Start

1. Onboard a New Agent

nemoclaw onboard

The interactive wizard prompts for:

  • Sandbox name (e.g. my-assistant)
  • NVIDIA API key ($NVIDIA_API_KEY)
  • Inference model selection
  • Network and filesystem policy configuration

Expected output on success:

──────────────────────────────────────────────────
Sandbox      my-assistant (Landlock + seccomp + netns)
Model        nvidia/nemotron-3-super-120b-a12b (NVIDIA Cloud API)
──────────────────────────────────────────────────
Run:         nemoclaw my-assistant connect
Status:      nemoclaw my-assistant status
Logs:        nemoclaw my-assistant logs --follow
──────────────────────────────────────────────────
[INFO]  === Installation complete ===

2. Connect to the Sandbox

nemoclaw my-assistant connect

3. Chat with the Agent (inside sandbox)

TUI (interactive chat):

sandbox@my-assistant:~$ openclaw tui

CLI (single message):

sandbox@my-assistant:~$ openclaw agent --agent main --local -m "hello" --session-id test

Key CLI Commands

Host Commands (nemoclaw)

Command Description
nemoclaw onboard Interactive setup: gateway, providers, sandbox
nemoclaw <name> connect Open interactive shell inside sandbox
nemoclaw <name> status Show NemoClaw-level sandbox health
nemoclaw <name> logs --follow Stream sandbox logs
nemoclaw start Start auxiliary services (Telegram bridge, tunnel)
nemoclaw stop Stop auxiliary services
nemoclaw deploy <instance> Deploy to remote GPU instance via Brev
openshell term Launch OpenShell TUI for monitoring and approvals

Plugin Commands (openclaw nemoclaw, run inside sandbox)

Show the whole skill (321 more lines)

Note: These are under active development — use nemoclaw host CLI as the primary interface.

Command Description
openclaw nemoclaw launch [--profile ...] Bootstrap OpenClaw inside OpenShell sandbox
openclaw nemoclaw status Show sandbox health, blueprint state, and inference
openclaw nemoclaw logs [-f] Stream blueprint execution and sandbox logs

OpenShell Inspection

# List all sandboxes at the OpenShell layer
openshell sandbox list

# Check specific sandbox
openshell sandbox inspect my-assistant

Architecture

NemoClaw orchestrates four components:

Component Role
Plugin TypeScript CLI: launch, connect, status, logs
Blueprint Versioned Python artifact: sandbox creation, policy, inference setup
Sandbox Isolated OpenShell container running OpenClaw with policy-enforced egress/filesystem
Inference NVIDIA cloud model calls routed through OpenShell gateway

Blueprint lifecycle:

  1. Resolve artifact
  2. Verify digest
  3. Plan resources
  4. Apply through OpenShell CLI

TypeScript Plugin Usage

NemoClaw exposes a programmatic TypeScript API for building custom integrations.

Import and Initialize

import { NemoClawClient } from '@nvidia/nemoclaw';

const client = new NemoClawClient({
  apiKey: process.env.NVIDIA_API_KEY!,
  model: process.env.NEMOCLAW_MODEL ?? 'nvidia/nemotron-3-super-120b-a12b',
});

Create a Sandbox Programmatically

import { NemoClawClient, SandboxConfig } from '@nvidia/nemoclaw';

async function createSandbox() {
  const client = new NemoClawClient({
    apiKey: process.env.NVIDIA_API_KEY!,
  });

  const config: SandboxConfig = {
    name: 'my-assistant',
    model: 'nvidia/nemotron-3-super-120b-a12b',
    policy: {
      network: {
        allowedEgressHosts: ['build.nvidia.com'],
        blockUnlisted: true,
      },
      filesystem: {
        allowedPaths: ['/sandbox', '/tmp'],
        readOnly: false,
      },
    },
  };

  const sandbox = await client.sandbox.create(config);
  console.log(`Sandbox created: ${sandbox.id}`);
  return sandbox;
}

Connect and Send a Message

import { NemoClawClient } from '@nvidia/nemoclaw';

async function chatWithAgent(sandboxName: string, message: string) {
  const client = new NemoClawClient({
    apiKey: process.env.NVIDIA_API_KEY!,
  });

  const sandbox = await client.sandbox.get(sandboxName);
  const session = await sandbox.connect();

  const response = await session.agent.send({
    agentId: 'main',
    message,
    sessionId: `session-${Date.now()}`,
  });

  console.log('Agent response:', response.content);
  await session.disconnect();
}

chatWithAgent('my-assistant', 'Summarize the latest NVIDIA earnings report.');

Check Sandbox Status

import { NemoClawClient } from '@nvidia/nemoclaw';

async function checkStatus(sandboxName: string) {
  const client = new NemoClawClient({
    apiKey: process.env.NVIDIA_API_KEY!,
  });

  const status = await client.sandbox.status(sandboxName);

  console.log({
    sandbox: status.name,
    healthy: status.healthy,
    blueprint: status.blueprintState,
    inference: status.inferenceProvider,
    policyVersion: status.policyVersion,
  });
}

Stream Logs

import { NemoClawClient } from '@nvidia/nemoclaw';

async function streamLogs(sandboxName: string) {
  const client = new NemoClawClient({
    apiKey: process.env.NVIDIA_API_KEY!,
  });

  const logStream = client.sandbox.logs(sandboxName, { follow: true });

  for await (const entry of logStream) {
    console.log(`[${entry.timestamp}] ${entry.level}: ${entry.message}`);
  }
}

Apply a Network Policy Update (Hot Reload)

import { NemoClawClient, NetworkPolicy } from '@nvidia/nemoclaw';

async function updateNetworkPolicy(sandboxName: string) {
  const client = new NemoClawClient({
    apiKey: process.env.NVIDIA_API_KEY!,
  });

  // Network policies are hot-reloadable at runtime
  const updatedPolicy: NetworkPolicy = {
    allowedEgressHosts: [
      'build.nvidia.com',
      'api.github.com',
    ],
    blockUnlisted: true,
  };

  await client.sandbox.updatePolicy(sandboxName, {
    network: updatedPolicy,
  });

  console.log('Network policy updated (hot reload applied).');
}

Security / Protection Layers

Layer What it protects Hot-reloadable?
Network Blocks unauthorized outbound connections ✅ Yes
Filesystem Prevents reads/writes outside /sandbox and /tmp ❌ Locked at creation
Process Blocks privilege escalation and dangerous syscalls ❌ Locked at creation
Inference Reroutes model API calls to controlled backends ✅ Yes

When the agent attempts to reach an unlisted host, OpenShell blocks the request and surfaces it in the TUI for operator approval.


Common Patterns

Pattern: Minimal Sandbox for Development

const config: SandboxConfig = {
  name: 'dev-sandbox',
  model: 'nvidia/nemotron-3-super-120b-a12b',
  policy: {
    network: { blockUnlisted: false },   // permissive for dev
    filesystem: { allowedPaths: ['/sandbox', '/tmp', '/home/dev'] },
  },
};

Pattern: Production Strict Sandbox

const config: SandboxConfig = {
  name: 'prod-assistant',
  model: 'nvidia/nemotron-3-super-120b-a12b',
  policy: {
    network: {
      allowedEgressHosts: ['build.nvidia.com'],
      blockUnlisted: true,
    },
    filesystem: {
      allowedPaths: ['/sandbox', '/tmp'],
      readOnly: false,
    },
  },
};

Pattern: Deploy to Remote GPU (Brev)

nemoclaw deploy my-gpu-instance --sandbox my-assistant
await client.deploy({
  instance: 'my-gpu-instance',
  sandboxName: 'my-assistant',
  provider: 'brev',
});

Troubleshooting

Error: Sandbox not found

Error: Sandbox 'my-assistant' not found

Fix: Check at the OpenShell layer — NemoClaw errors and OpenShell errors are separate:

openshell sandbox list
nemoclaw my-assistant status

Error: NVIDIA API key missing or invalid

Error: Inference provider authentication failed

Fix:

export NVIDIA_API_KEY="nvapi-xxxxxxxxxxxx"
nemoclaw onboard  # re-run to reconfigure

Error: Docker not running

Error: Cannot connect to Docker daemon

Fix:

sudo systemctl start docker
sudo usermod -aG docker $USER  # add current user to docker group
newgrp docker

Error: OpenShell not installed

Error: 'openshell' command not found

Fix: Install NVIDIA OpenShell first, then re-run the NemoClaw installer.

Agent blocked on outbound request

When you see a blocked request notification in the TUI:

openshell term        # open TUI to approve/deny the request
# OR update policy to allow the host:
nemoclaw my-assistant policy update --allow-host api.example.com

View Full Debug Logs

nemoclaw my-assistant logs --follow
# or with verbose flag
nemoclaw my-assistant logs --follow --level debug

Documentation Links