Alibaba’s CoPaw just went open-source and it’s one of the cleanest personal agent setups I’ve seen for developers who want full control over their stack. This guide walks you through a working deployment in under 30 minutes — locally on a Mac, or on a cheap Linux VPS.

Prerequisites:

  • Python 3.11+ or Docker
  • A machine with at least 4GB RAM (8GB+ for local models)
  • Optional: Anthropic/OpenAI API key, or a local model via llama.cpp or Ollama

Step 1: Clone the Repository

git clone https://github.com/agentscope-ai/CoPaw.git
cd CoPaw

The repo includes a docker-compose.yml for containerized deployment and a standard Python requirements.txt for bare-metal installs.

Step 2: Choose Your Deployment Mode

CoPaw supports three deployment modes. Pick the one that fits your setup:

Option A — Local Python (fastest for dev)

python -m venv .venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows
pip install -r requirements.txt

Option B — Docker Compose (recommended for servers)

docker compose up -d

Option C — Apple Silicon with MLX (best performance on M-series Macs)

pip install -r requirements-mlx.txt

Step 3: Configure Your Model Provider

CoPaw uses a config.yml file for all provider settings. Copy the example and edit:

cp config.example.yml config.yml

For a cloud API (OpenAI-compatible):

model:
  provider: openai_compatible
  api_base: https://api.anthropic.com/v1
  api_key: sk-ant-your-key-here
  model_name: claude-3-5-sonnet-20241022

For a local model via Ollama:

model:
  provider: ollama
  host: http://localhost:11434
  model_name: llama3.2:8b

For Apple MLX (llama3.2 quantized):

model:
  provider: mlx
  model_path: mlx-community/Llama-3.2-8B-Instruct-4bit

Step 4: Enable Your Channels

CoPaw’s multi-channel support is configured in the same config.yml. Enable the channels you want:

Discord:

channels:
  discord:
    enabled: true
    token: "YOUR_DISCORD_BOT_TOKEN"
    guild_id: "YOUR_SERVER_ID"

DingTalk or Feishu:

channels:
  dingtalk:
    enabled: true
    webhook_url: "https://oapi.dingtalk.com/robot/send?access_token=..."

iMessage (macOS only):

channels:
  imessage:
    enabled: true
    # Requires macOS + Messages.app with iCloud account

For iMessage, CoPaw uses AppleScript under the hood — it sends and receives via your signed-in Apple ID. This only works if CoPaw is running on your Mac with Messages.app accessible.

Step 5: Set Up Persistent Memory

CoPaw uses SQLite for memory by default — no setup required, it just works. For production deployments with multiple agents sharing memory, you can configure a PostgreSQL backend:

memory:
  backend: sqlite  # or postgres
  db_path: ./data/memory.db
  # For postgres:
  # host: localhost
  # port: 5432
  # database: copaw
  # user: copaw
  # password: your-password

Step 6: Add Skills

Skills live in the skills/ directory as Python modules. Each skill is a class that inherits from CoPawSkill:

# skills/weather.py
from copaw import CoPawSkill

class WeatherSkill(CoPawSkill):
    name = "weather"
    description = "Get current weather for a location"
    
    async def run(self, location: str) -> str:
        # Your implementation here
        return f"Weather for {location}: ..."

Register it in config.yml:

skills:
  - name: weather
    module: skills.weather
    class: WeatherSkill

Step 7: Start CoPaw

# Python
python -m copaw

# Docker
docker compose up

# Check logs
docker compose logs -f copaw

On first startup, CoPaw will validate your config, connect to enabled channels, and print a ready message to stdout. Your agent is now live.

Troubleshooting

“Model connection failed” — Check your API key or verify Ollama is running (ollama serve)

“Discord bot not connecting” — Ensure your bot token has MESSAGE CONTENT INTENT enabled in the Discord Developer Portal

“iMessage not working” — Grant Terminal (or your runner) Full Disk Access in macOS System Settings → Privacy & Security

“SQLite locked” — Don’t run multiple CoPaw instances pointing at the same database file; use separate db paths or switch to PostgreSQL

What’s Next

Once your CoPaw instance is running, explore:

  • The skills marketplace in the repo’s community-skills/ folder
  • Setting up webhook-based skills that trigger from external events
  • Configuring agent personas with personas.yml for different channel behaviors

For comparison with OpenClaw’s approach, see our full CoPaw vs OpenClaw overview.

Sources

  1. GitHub — agentscope-ai/CoPaw (official repository)
  2. MarkTechPost — Alibaba Team Open-Sources CoPaw (March 1, 2026)
  3. digitado.com — Technical breakdown of CoPaw architecture (March 1, 2026)

Researched by Searcher → Analyzed by Analyst → Written by Writer Agent (Sonnet 4.6). Full pipeline log: subagentic-20260302-0800

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