DeployOpenClawFebruary 23, 2026·8 min read

Deploy OpenClaw on Mac Mini: Your Always-On AI Agent (2026)

The Mac Mini is one of the best machines for running OpenClaw agents around the clock. It is silent, draws minimal power, and has enough horsepower to run local models. This guide walks you through everything from installation to remote access so your agents never go offline.

Why Mac Mini for OpenClaw?

Running OpenClaw on your laptop works for testing, but the moment you close the lid or put your machine to sleep, your agents go dark. If you rely on agents for Telegram notifications, Slack monitoring, or scheduled data pulls, you need a dedicated machine that stays on.

The Mac Mini checks every box for an always-on agent server:

Always on, always quiet

The Mac Mini has no moving parts in its fanless Apple Silicon variants. It sits on a shelf, draws 5-15 watts at idle, and runs 24/7 without producing any noise. You can place it in a living room or office and forget it is there.

Powerful enough for local models

Apple Silicon's unified memory architecture means the GPU and CPU share the same RAM pool. An M1 Mac Mini with 16GB can run 7B parameter models through Ollama at usable speeds. An M4 with 24GB can handle 13B models comfortably.

macOS stability

macOS is reliable for long-running processes. Combined with launchd for service management, your OpenClaw gateway will restart automatically after updates, power outages, or unexpected crashes.

Low total cost of ownership

A refurbished M1 Mac Mini starts around $350. Electricity costs roughly $2 per month. Compare that to a VPS with 16GB RAM at $50 to $80 per month. The Mac Mini pays for itself within 6 months.

Hardware Requirements

Any Mac Mini from 2020 onward will work. Here is what to look for depending on your use case:

Use CaseChipRAMStorage
Cloud LLMs only (Claude, GPT-4)M1 or newer8GB256GB SSD
Local 7B models (Ollama)M1 or newer16GB256GB SSD
Local 13B+ models + multi-agentM2 / M424GB+512GB SSD

The M1 Mac Mini (2020) with 16GB RAM is the sweet spot for most users. It handles cloud-based LLM agents effortlessly and can run smaller local models when needed. You can find refurbished units for $400-500.

Installation Steps

Start with a fresh macOS installation or your existing setup. OpenClaw requires Node.js 18 or later.

Step 1: Install prerequisites
# Install Homebrew (if not already installed)
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# Install Node.js
brew install node

# Verify installation
node --version  # Should be v18 or later
npm --version
Step 2: Install OpenClaw
# Install OpenClaw globally
npm install -g openclaw

# Verify OpenClaw is installed
openclaw --version

# Set your LLM API key
export ANTHROPIC_API_KEY="sk-ant-your-key-here"
# or for OpenAI:
export OPENAI_API_KEY="sk-your-key-here"
Step 3: Initialize your workspace
# Create a directory for your agents
mkdir -p ~/openclaw-server/agents
cd ~/openclaw-server

# Initialize OpenClaw
openclaw init

That is the foundation. OpenClaw is installed, your API key is configured, and you have a workspace ready for agents.

Creating Your Agent

Every OpenClaw agent starts with a SOUL.md file. Here is an example of a BI analyst agent that monitors your business metrics and answers questions about your data:

agents/bi-analyst/SOUL.md
# BI Analyst

## Identity
- Name: Atlas
- Role: Business Intelligence Analyst
- Model: claude-sonnet-4-20250514

## Personality
- Data-driven and precise
- Explains metrics in plain language
- Proactively flags anomalies and trends
- Responds with tables and charts when appropriate

## Rules
- Always include the date range in your analysis
- Compare current metrics against the previous period
- Flag any metric that changed more than 20% as notable
- When asked about revenue, include both gross and net figures
- Never share raw API keys or credentials in responses

## Skills
- browser: Search the web for industry benchmarks
- file-manager: Read and write CSV reports

## Channels
- telegram: Receive questions and send reports via Telegram

## Data Context
You have access to the following data sources through scripts:
- GA4 analytics (traffic, sessions, conversions)
- Mixpanel events (funnel, retention, feature usage)
- Stripe financials (MRR, churn, LTV)

When asked for a report, run the appropriate script and
summarize the results with key insights.
Register and start the agent
# Register the agent
openclaw agents add bi-analyst --workspace ./agents/bi-analyst

# Start the gateway
openclaw gateway start

# Test with a direct message
openclaw agent --agent bi-analyst --message "What is our MRR trend?"

Your BI analyst agent is now running. It understands its role, knows what data sources are available, and can communicate through Telegram. The entire setup is a single markdown file.

Connecting Data Sources

An agent without data is just a chatbot. The real power of a Mac Mini deployment is connecting your agent to live data sources through scripts. Here are the most common integrations:

Google Analytics 4

scripts/ga4-traffic.cjs
const { BetaAnalyticsDataClient } = require(
  "@google-analytics/data"
);

const client = new BetaAnalyticsDataClient({
  keyFilename: "./credentials/ga4-service-account.json",
});

async function getTraffic(propertyId, days = 7) {
  const [response] = await client.runReport({
    property: `properties/${propertyId}`,
    dateRanges: [{ startDate: `${days}daysAgo`, endDate: "today" }],
    metrics: [
      { name: "sessions" },
      { name: "totalUsers" },
      { name: "conversions" },
    ],
    dimensions: [{ name: "date" }],
  });
  return response.rows;
}

module.exports = { getTraffic };

Mixpanel Events

scripts/mixpanel-funnel.cjs
const fetch = require("node-fetch");

async function getFunnelData(projectSecret, fromDate, toDate) {
  const auth = Buffer.from(`${projectSecret}:`).toString("base64");
  const response = await fetch(
    `https://data.mixpanel.com/api/2.0/export?` +
    `from_date=${fromDate}&to_date=${toDate}`,
    { headers: { Authorization: `Basic ${auth}` } }
  );
  return response.json();
}

module.exports = { getFunnelData };

Stripe Financials

scripts/stripe-report.cjs
const Stripe = require("stripe");
const stripe = new Stripe(process.env.STRIPE_SECRET_KEY);

async function getMRR() {
  const subscriptions = await stripe.subscriptions.list({
    status: "active",
    limit: 100,
  });

  const mrr = subscriptions.data.reduce((sum, sub) => {
    return sum + sub.items.data[0].price.unit_amount / 100;
  }, 0);

  return { mrr, activeCount: subscriptions.data.length };
}

module.exports = { getMRR };

Store these scripts in your workspace directory. Your agent can reference them through its Skills or through direct file access. The Mac Mini runs these scripts locally, so your API credentials never leave your machine.

Running as a Background Service

Running OpenClaw in a terminal window works, but it stops when you close the session. For a true always-on setup, configure the gateway as a macOS launchd service. This ensures the gateway starts on boot and restarts if it crashes.

~/Library/LaunchAgents/ai.openclaw.gateway.plist
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN"
  "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
  <key>Label</key>
  <string>ai.openclaw.gateway</string>

  <key>ProgramArguments</key>
  <array>
    <string>/usr/local/bin/node</string>
    <string>/usr/local/bin/openclaw</string>
    <string>gateway</string>
    <string>start</string>
  </array>

  <key>WorkingDirectory</key>
  <string>/Users/yourusername/openclaw-server</string>

  <key>EnvironmentVariables</key>
  <dict>
    <key>ANTHROPIC_API_KEY</key>
    <string>sk-ant-your-key-here</string>
    <key>PATH</key>
    <string>/usr/local/bin:/usr/bin:/bin</string>
  </dict>

  <key>RunAtLoad</key>
  <true/>

  <key>KeepAlive</key>
  <true/>

  <key>StandardOutPath</key>
  <string>/tmp/openclaw-gateway.log</string>

  <key>StandardErrorPath</key>
  <string>/tmp/openclaw-gateway-error.log</string>
</dict>
</plist>
Load and manage the service
# Load the service (starts immediately)
launchctl load ~/Library/LaunchAgents/ai.openclaw.gateway.plist

# Check if it is running
launchctl list | grep openclaw

# View logs
tail -f /tmp/openclaw-gateway.log

# Stop the service
launchctl unload ~/Library/LaunchAgents/ai.openclaw.gateway.plist

# Restart (unload then load)
launchctl unload ~/Library/LaunchAgents/ai.openclaw.gateway.plist
launchctl load ~/Library/LaunchAgents/ai.openclaw.gateway.plist

With RunAtLoad set to true, the gateway starts every time you log in. With KeepAlive set to true, macOS restarts it if the process dies. Also enable "Start up automatically after a power failure" in System Settings to handle power outages.

Accessing Remotely

Your agents are running on the Mac Mini, but you need to interact with them from your laptop, phone, or anywhere else. There are three approaches:

SSH Access

Enable Remote Login in System Settings under Sharing. This lets you SSH into your Mac Mini from any machine on the same network and run OpenClaw commands directly.

SSH into Mac Mini and interact with agents
# From your laptop
ssh yourusername@mac-mini.local

# Send a message to your agent
openclaw agent --agent bi-analyst --message "Send me today's revenue report"

# Check gateway status
launchctl list | grep openclaw

Tailscale for Remote Access

SSH works on your local network. For access from anywhere, install Tailscale on both the Mac Mini and your devices. Tailscale creates a private mesh VPN with zero configuration. Once connected, your Mac Mini gets a stable IP address you can SSH into from a coffee shop, hotel, or your phone.

Install and use Tailscale
# Install Tailscale on Mac Mini
brew install tailscale
tailscale up

# Now from any device on your Tailscale network:
ssh yourusername@mac-mini  # Uses Tailscale hostname

# Access the OpenClaw gateway dashboard
# Open in browser: http://mac-mini:18789

OpenClaw Gateway Dashboard

The OpenClaw gateway runs a web dashboard on port 18789 by default. Through Tailscale or on your local network, open http://mac-mini.local:18789 in your browser to see agent status, session history, and real-time logs. This is the easiest way to monitor your agents without touching the terminal.

Telegram as Your Remote Interface

The most practical remote access method is the one already in your pocket. Configure Telegram as a channel in your agent's SOUL.md, and you can message your agents from your phone anywhere in the world. No VPN, no SSH, no port forwarding. Your agent receives the message through the Telegram Bot API and responds in the same chat.

Mac Mini vs Raspberry Pi vs VPS

The Mac Mini is not the only option for an always-on OpenClaw server. Here is how it compares to the two most common alternatives:

FeatureMac Mini (M1/M2/M4)Raspberry Pi 5VPS (4GB-16GB)
RAM8GB - 32GB unified4GB - 8GB4GB - 16GB
Upfront cost$350 - $800$60 - $120$0
Monthly cost$2 - $5 (electricity)$1 - $2 (electricity)$20 - $80
Local model supportExcellent (Ollama, GPU accel.)Poor (no GPU, slow inference)None (unless GPU VPS at $100+/mo)
CPU performanceHigh (Apple Silicon)Low (ARM Cortex-A76)Medium (shared vCPU)
Power consumption5 - 40W3 - 12WN/A (cloud)
Data privacyFull (local machine)Full (local machine)Limited (hosted by provider)
Setup complexityLow (macOS, Homebrew)Medium (Linux, manual config)Medium (SSH, Linux admin)
Best forAlways-on agents + local modelsBudget setups, cloud LLMs onlyTeams needing uptime SLAs

The Mac Mini wins on performance-per-dollar for most agent workloads. The Raspberry Pi is the budget option if you only use cloud-based LLMs and need a simple always-on machine. A VPS makes sense when you need guaranteed uptime, a static public IP, or when your team is distributed and you do not want to maintain physical hardware.

Skip the Setup with CrewClaw

Setting up a Mac Mini server, writing SOUL.md files, configuring launchd, and connecting data sources takes time. If you want a working OpenClaw agent in minutes instead of hours, CrewClaw generates your complete agent configuration for you.

Pick a role from our library of pre-built templates, customize the personality and skills, and download your agent package. The package includes a ready-to-deploy SOUL.md, a launchd plist for background service setup, and documentation. You can have your Mac Mini running a production agent in under 10 minutes.

Frequently Asked Questions

Can I run OpenClaw on an Intel Mac Mini?

Yes, OpenClaw runs on Intel Mac Minis. However, Apple Silicon models (M1, M2, M4) are recommended because they offer significantly better performance per watt and can run local models through Ollama more efficiently. An Intel Mac Mini will work fine for cloud-based LLM providers like Claude and GPT-4, but local model inference will be noticeably slower.

How much does it cost to run a Mac Mini as an always-on server?

A Mac Mini with Apple Silicon draws between 5 and 15 watts at idle, which translates to roughly $1 to $3 per month in electricity depending on your local rates. Under sustained load with Ollama running local models, power draw increases to 30-40 watts, still well under $10 per month. This is significantly cheaper than a VPS with comparable performance.

Do I need to keep a monitor connected to the Mac Mini?

No. macOS runs headless without a monitor. After initial setup, you can manage the Mac Mini entirely over SSH or through screen sharing. Some users plug in an HDMI dummy dongle to maintain full GPU resolution for screen sharing, but it is not required for OpenClaw since the gateway runs as a terminal process.

Can I run multiple OpenClaw agents on a single Mac Mini?

Yes. The OpenClaw gateway supports multiple agents simultaneously. A Mac Mini with 8GB of RAM can comfortably run 3 to 5 agents using cloud-based LLMs. If you use Ollama for local inference, each loaded model consumes additional memory, so a 16GB or 24GB model is recommended for running more than one local model at a time alongside your agents.

What happens if my Mac Mini restarts unexpectedly?

If you configure the OpenClaw gateway as a launchd service as described in this guide, macOS will automatically restart the gateway process after a reboot. You should also enable automatic restart after power failure in System Settings under Energy Saver. With both settings configured, your agents will come back online within 60 seconds of the Mac Mini booting up.

Is a Mac Mini better than a Raspberry Pi for OpenClaw?

For most use cases, yes. The Mac Mini has significantly more processing power, more RAM options (up to 24GB or 32GB), faster SSD storage, and can run local models through Ollama. A Raspberry Pi is cheaper upfront but limited to 8GB RAM, has no GPU acceleration for local inference, and runs on ARM Linux which can have compatibility issues with some Node.js packages. Choose a Raspberry Pi only if budget is the primary concern and you plan to use cloud-based LLMs exclusively.

Build your OpenClaw agent with CrewClaw

Skip the manual configuration. CrewClaw generates your SOUL.md, deploy scripts, and agent package in minutes. Pick a role, customize, and download.