> 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. # Overview of NVIDIA NemoClaw > NemoClaw is an open-source reference stack that simplifies running OpenClaw always-on assistants more safely. NVIDIA NemoClaw is an open-source reference stack that simplifies running [OpenClaw](https://openclaw.ai) always-on assistants more safely. NemoClaw provides onboarding, lifecycle management, and OpenClaw operations within OpenShell containers. It incorporates policy-based privacy and security guardrails, giving you control over your agents’ behavior and data handling. This enables self-evolving claws to run more safely in clouds, on prem, RTX PCs and DGX Spark. NemoClaw pairs hosted models on inference providers or local endpoints with a hardened sandbox, routed inference, and declarative egress policy so deployment stays safer and more repeatable. The sandbox runtime comes from [NVIDIA OpenShell](https://github.com/NVIDIA/OpenShell); NemoClaw adds the blueprint, `nemoclaw` CLI, onboarding, and related tooling as the reference way to run OpenClaw there. | Capability | Description | | -------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Sandbox OpenClaw | Creates an OpenShell sandbox pre-configured for OpenClaw, with filesystem and network policies applied from the first boot. | | Route inference | Configures OpenShell inference routing so agent traffic goes to the provider and model you chose during onboarding (NVIDIA Endpoints, OpenAI, Anthropic, Gemini, compatible endpoints, local Ollama, and others). The agent uses `inference.local` inside the sandbox; credentials stay on the host. | | Manage the lifecycle | Handles blueprint versioning, digest verification, and sandbox setup. | ## Key Features NemoClaw provides the following product capabilities. | Feature | Description | | ------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Guided onboarding | Validates credentials, selects providers, and creates a working sandbox in one command. | | Hardened blueprint | A security-first Dockerfile with capability drops, least-privilege network rules, and declarative policy. | | State management | Safe migration of agent state across machines with credential stripping and integrity verification. | | Messaging channels | OpenShell-managed processes connect Telegram, Discord, Slack, and similar platforms to the sandboxed agent. NemoClaw configures channels during onboarding; OpenShell supplies the native constructs, credential flow, and runtime supervision. | | Routed inference | Provider-routed model calls through the OpenShell gateway, transparent to the agent. Supports NVIDIA Endpoints, OpenAI, Anthropic, Google Gemini, compatible endpoints, local Ollama, local vLLM, and the Model Router. | | Layered protection | Network, filesystem, process, and inference controls that can be hot-reloaded or locked at creation. | ## Benefits of Using NemoClaw Autonomous AI agents can make arbitrary network requests, access the host filesystem, and call any inference endpoint. Without guardrails, this creates security, cost, and compliance risks that grow as agents run unattended. NemoClaw provides the following benefits to mitigate these risks. | Benefit | Description | | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Sandboxed execution | Every agent runs inside an OpenShell sandbox with Landlock, seccomp, and network namespace isolation. No access is granted by default. | | Routed inference | Model traffic is routed through the OpenShell gateway to your selected provider, transparent to the agent. You can switch providers or models. Refer to [Inference Options](/inference/inference-options). | | Declarative network policy | Egress rules are defined in YAML. Unknown hosts are blocked and surfaced to the operator for approval. | | Single CLI | The `nemoclaw` command orchestrates the full stack: gateway, sandbox, inference provider, and network policy. | | Blueprint lifecycle | Versioned blueprints handle sandbox creation, digest verification, and reproducible setup. | ## Use Cases You can use NemoClaw for various use cases including the following. | Use Case | Description | | --------------------- | -------------------------------------------------------------------------------------- | | Always-on assistant | Run an OpenClaw assistant with controlled network access and operator-approved egress. | | Sandboxed testing | Test agent behavior in a locked-down environment before granting broader permissions. | | Remote GPU deployment | Deploy a sandboxed agent to a remote GPU instance for persistent operation. | ## Next Steps Navigate to the following topics to learn more about NemoClaw and how to install and use it. * [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. * [Quickstart](/get-started/quickstart) to install NemoClaw and run your first sandboxed agent. * [Inference Options](/inference/inference-options) to check the inference providers that NemoClaw supports and how inference routing works.