MR
Mayur Rathi
@sickn33
⭐ 47.3k GitHub stars

openclaw-local-mac-mini

openclaw-local-mac-mini is an engineering AI skill with a core value of Set up OpenClaw locally and run it reliably on a Mac mini for private, always-on local agent workflows. It helps developers solve real-world problems in the engineering domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

Set up OpenClaw locally and run it reliably on a Mac mini for private, always-on local agent workflows.

Last verified on: 2026-10-06

Quick Facts

Category engineering
Works With Claude
Source sickn33/antigravity-awesome-skills
Stars ⭐ 47.3k
Last Verified 2026-10-06
Risk Level Low
mkdir -p ./skills/openclaw-local-mac-mini && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/openclaw-local-mac-mini/SKILL.md -o ./skills/openclaw-local-mac-mini/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# OpenClaw Local + Mac mini Setup


Use this skill when you want to run [OpenClaw](https://github.com/openclaw/openclaw) on a developer laptop or promote it to a stable Mac mini host. Covers cloning and bootstrapping, Docker Compose configuration, Mac mini hardware optimization, networking, monitoring, and production-grade launchd services.


Prerequisites


- macOS 13 (Ventura) or later on Apple Silicon (M1/M2/M4 Mac mini recommended)

- Docker Desktop for Mac or OrbStack installed

- Git, Node.js (v18+), and a package manager (npm or pnpm)

- API keys for your chosen LLM provider (OpenAI, Anthropic, or local Ollama)

- At least 16 GB RAM (32 GB recommended for local model serving)


Local Setup (Any Dev Machine)


Clone and Bootstrap


bash
# Clone the repository
git clone https://github.com/openclaw/openclaw.git
cd openclaw

# Review the upstream README for current prerequisites
cat README.md

# Copy the example environment file
cp .env.example .env

# Edit .env with your provider keys and configuration
# At minimum, set the model provider and API key
cat > .env << 'ENV'
# LLM Provider Configuration
OPENAI_API_KEY=sk-your-openai-key-here
# Or for Anthropic:
# ANTHROPIC_API_KEY=sk-ant-your-key-here
# Or for local Ollama:
# OLLAMA_BASE_URL=http://localhost:11434

# Application settings
NODE_ENV=development
PORT=3000
HOST=0.0.0.0
LOG_LEVEL=info

# Database (if applicable)
DATABASE_URL=sqlite:./data/openclaw.db
ENV

Install Dependencies and Run


bash
# Install dependencies
npm install
# Or with pnpm:
# pnpm install

# Run database migrations if needed
npm run db:migrate

# Start the development server
npm run dev

# Verify startup
curl -s http://localhost:3000/api/health | jq .
# Expected: {"status":"ok","version":"..."}

Validate the Setup


bash
# Check the API health endpoint
curl -f http://localhost:3000/api/health

# Check the UI loads
curl -s -o /dev/null -w '%{http_code}' http://localhost:3000/
# Expected: 200

# Run built-in tests if available
npm test

Docker Compose Setup


docker-compose.yml


yaml
version: "3.8"

services:
  openclaw:
    build:
      context: .
      dockerfile: Dockerfile
    image: openclaw:latest
    container_name: openclaw
    restart: unless-stopped
    ports:
      - "3000:3000"
    env_file:
      - .env
    environment:
      - NODE_ENV=production
      - HOST=0.0.0.0
      - PORT=3000
    volumes:
      - openclaw-data:/app/data
      - ./config:/app/config:ro
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:3000/api/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 15s
    deploy:
      resources:
        limits:
          memory: 4G
        reservations:
          memory: 1G
    logging:
      driver: json-file
      options:
        max-size: "50m"
        max-file: "5"

  # Optional: Redis for caching/queues
  redis:
    image: redis:7-alpine
    container_name: openclaw-redis
    restart: unless-stopped
    volumes:
      - redis-data:/data
    command: redis-server --appendonly yes --maxmemory 512mb --maxmemory-policy allkeys-lru
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 5s
      retries: 3

  # Optional: Ollama for local model serving
  ollama:
    image: ollama/ollama:latest
    container_name: openclaw-ollama
    restart: unless-stopped
    ports:
      - "11434:11434"
    volumes:
      - ollama-models:/root/.ollama
    deploy:
      resources:
        limits:
          memory: 16G
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:11434/api/tags"]
      interval: 30s
      timeout: 10s
      retries: 3

volumes:
  openclaw-data:
  redis-data:
  ollama-models:

Running with Docker Compose


bash
# Build and start all services
docker compose up -d --build

# Check service status
docker compose ps

# View logs
docker compose logs -f openclaw
docker compose logs -f --tail=100 ollama

# Pull a model into Ollama (if 

🎯 Best For

  • Claude users
  • AI users

💡 Use Cases

  • Using openclaw-local-mac-mini in daily workflow
  • Automating repetitive engineering tasks

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply openclaw-local-mac-mini to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

How do I install openclaw-local-mac-mini?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/openclaw-local-mac-mini/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Not reading the full skill

Skills contain important context and edge cases beyond the quick start.

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