moorcheh-ai Memantoclaw Overview
Learn how MemantoClaw combines a lightweight CLI plugin with a versioned blueprint to move OpenClaw into a controlled sandbox.
Context
MemantoClaw combines a lightweight CLI plugin with a versioned blueprint to move OpenClaw into a controlled sandbox. This page explains the key concepts about MemantoClaw at a high level.
How It Fits Together
The memantoclaw CLI is the primary entrypoint for setting up and managing sandboxed OpenClaw agents.
It delegates heavy lifting to a versioned blueprint, a Python artifact that orchestrates sandbox creation, policy application, and inference provider setup through the OpenShell CLI.
flowchart TB
subgraph Host
CMD["memantoclaw onboard"]
PLUGIN[memantoclaw plugin]
BLUEPRINT[blueprint runner]
CLI["openshell CLI sandbox · gateway · inference · policy"]
CMD --> PLUGIN
PLUGIN --> BLUEPRINT
BLUEPRINT --> CLI
end
subgraph Sandbox["OpenShell Sandbox"]
AGENT[OpenClaw agent]
INF[NVIDIA inference, routed]
NET[default network policy]
FS[filesystem isolation]
AGENT --- INF
AGENT --- NET
AGENT --- FS
end
PLUGIN --> AGENT
classDef nv fill:#76b900,stroke:#333,color:#fff
classDef nvLight fill:#e6f2cc,stroke:#76b900,color:#1a1a1a
classDef nvDark fill:#333,stroke:#76b900,color:#fff
class CMD,PLUGIN,BLUEPRINT nvDark
class CLI nv
class AGENT nv
class INF,NET,FS nvLight
style Host fill:none,stroke:#76b900,stroke-width:2px,color:#1a1a1a
style Sandbox fill:#f5faed,stroke:#76b900,stroke-width:2px,color:#1a1a1a
Design Principles
MemantoClaw architecture follows the following principles.
Thin plugin, versioned blueprint : The plugin stays small and stable. Orchestration logic lives in the blueprint and evolves on its own release cadence.
Respect CLI boundaries
: The memantoclaw CLI is the primary interface for sandbox management.
Supply chain safety : Blueprint artifacts are immutable, versioned, and digest-verified before execution.
Full details in references/how-it-works.md.
Alpha software: MemantoClaw is in alpha, available as an early preview since March 16, 2026. APIs, configuration schemas, and runtime behavior are subject to breaking changes between releases. Do not use this software in production environments. File issues and feedback through the GitHub repository as the project continues to stabilize.
Moorcheh MemantoClaw is an open source reference stack that simplifies running OpenClaw always-on assistants. It incorporates policy-based privacy and security guardrails, giving users control over their agents’ behavior and data handling. This enables self-evolving claws to run more safely in clouds, on prem, RTX PCs and DGX Spark.
MemantoClaw uses open source models, such as NVIDIA Nemotron, alongside the NVIDIA OpenShell runtime, part of the NVIDIA Agent Toolkit—a secure environment designed for executing claws more safely. By combining powerful open source models with built-in safety measures, MemantoClaw simplifies and secures AI agent deployment.
| 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 flows through cloud-hosted Nemotron 3 Super 120B via build.nvidia.com. |
| Manage the lifecycle | Handles blueprint versioning, digest verification, and sandbox setup. |
Challenge
Autonomous AI agents like OpenClaw 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.
Benefits
MemantoClaw provides the following benefits.
| Benefit | Description |
|---|---|
| Sandboxed execution | Every agent runs inside an OpenShell sandbox with Landlock, seccomp, and network namespace isolation. No access is granted by default. |
| NVIDIA Endpoint inference | Agent traffic routes through cloud-hosted Nemotron 3 Super 120B via build.nvidia.com, transparent to the agent. |
| Declarative network policy | Egress rules are defined in YAML. Unknown hosts are blocked and surfaced to the operator for approval. |
| Single CLI | The memantoclaw 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 MemantoClaw 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. |
Reference
- MemantoClaw Release Notes
Related Skills
memantoclaw-get-started— Quickstart to install MemantoClaw and run your first agentmemantoclaw-configure-inference— Switch Inference Providers to configure the inference providermemantoclaw-manage-policy— Approve or Deny Network Requests to manage egress approvalsmemantoclaw-deploy-remote— Deploy to a Remote GPU Instance for persistent operationmemantoclaw-monitor-sandbox— Monitor Sandbox Activity to observe agent behavior