memantoclaw-get-started

name	memantoclaw-get-started
description	Installs MemantoClaw, launch a sandbox, and run your first agent prompt. Use when inference routing, install memantoclaw openclaw sandbox, memantoclaw, memantoclaw quickstart, memantoclaw quickstart install launch, openclaw, openshell, sandboxing.

Memantoclaw Get Started

Install MemantoClaw, launch a sandbox, and run your first agent prompt.

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.

Follow these steps to get started with MemantoClaw and your first sandboxed OpenClaw agent.

Note: MemantoClaw currently requires a fresh installation of OpenClaw.

Prerequisites

Check the prerequisites before you start to ensure you have the necessary software and hardware to run MemantoClaw.

Hardware

Resource	Minimum	Recommended
CPU	4 vCPU	4+ vCPU
RAM	8 GB	16 GB
Disk	20 GB free	40 GB free

The sandbox image is approximately 2.4 GB compressed. During image push, the Docker daemon, k3s, and the OpenShell gateway run alongside the export pipeline, which buffers decompressed layers in memory. On machines with less than 8 GB of RAM, this combined usage can trigger the OOM killer. If you cannot add memory, configuring at least 8 GB of swap can work around the issue at the cost of slower performance.

Software

Dependency	Version
Linux	Ubuntu 22.04 LTS or later
Node.js	20 or later
npm	10 or later
Container runtime	Supported runtime installed and running
OpenShell	Installed

Container Runtime Support

Platform	Supported runtimes	Notes
Linux	Docker	Primary supported path today
macOS (Apple Silicon)	Colima, Docker Desktop	Recommended runtimes for supported macOS setups
macOS	Podman	Not supported yet. MemantoClaw currently depends on OpenShell support for Podman on macOS.
Windows WSL	Docker Desktop (WSL backend)	Supported target path

💡 Tip

For DGX Spark, follow the DGX Spark setup guide. It covers Spark-specific prerequisites, such as cgroup v2 and Docker configuration, before running the standard installer.

Install MemantoClaw 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.

curl -fsSL https://raw.githubusercontent.com/moorcheh-ai/memantoclaw/refs/heads/main/install.sh | bash

If you use nvm or fnm to manage Node.js, the installer may not update your current shell's PATH. If memantoclaw is not found after install, run source ~/.bashrc (or source ~/.zshrc for zsh) or open a new terminal.

When the install completes, a summary confirms the running environment:

──────────────────────────────────────────────────
Sandbox      my-assistant (Landlock + seccomp + netns)
Model        nvidia/nemotron-3-super-120b-a12b (NVIDIA Endpoints)
──────────────────────────────────────────────────
Run:         memantoclaw my-assistant connect
Status:      memantoclaw my-assistant status
Logs:        memantoclaw my-assistant logs --follow
──────────────────────────────────────────────────

[INFO]  === Installation complete ===

Chat with the Agent

Connect to the sandbox, then chat with the agent through the TUI or the CLI.

Connect to the Sandbox

Run the following command to connect to the sandbox:

memantoclaw my-assistant connect

This connects you to the sandbox shell sandbox@my-assistant:~$ where you can run openclaw commands.

OpenClaw TUI

In the sandbox shell, run the following command to open the OpenClaw TUI, which opens an interactive chat interface.

openclaw tui

Send a test message to the agent and verify you receive a response.

ℹ️ Note

The TUI is best for interactive back-and-forth. If you need the full text of a long response such as a large code generation output, use the CLI instead.

OpenClaw CLI

In the sandbox shell, run the following command to send a single message and print the response:

openclaw agent --agent main --local -m "hello" --session-id test

This prints the complete response directly in the terminal and avoids relying on the TUI view for long output.

Uninstall

To remove MemantoClaw and all resources created during setup, in the terminal outside the sandbox, run:

curl -fsSL https://raw.githubusercontent.com/moorcheh-ai/memantoclaw/refs/heads/main/uninstall.sh | bash

The script removes sandboxes, the MemantoClaw gateway and providers, related Docker images and containers, local state directories, and the global memantoclaw npm package. It does not remove shared system tooling such as Docker, Node.js, npm, or Ollama.

Flag	Effect
--yes	Skip the confirmation prompt.
--keep-openshell	Leave the openshell binary installed.
--delete-models	Also remove MemantoClaw-pulled Ollama models.

For example, to skip the confirmation prompt:

curl -fsSL https://raw.githubusercontent.com/moorcheh-ai/memantoclaw/refs/heads/main/uninstall.sh | bash -s -- --yes

Related Skills

• memantoclaw-configure-inference — Switch inference providers to use a different model or endpoint
• memantoclaw-manage-policy — Approve or deny network requests when the agent tries to reach external hosts
• memantoclaw-deploy-remote — Deploy to a remote GPU instance for always-on operation
• memantoclaw-monitor-sandbox — Monitor sandbox activity through the OpenShell TUI