CoPaw

Works for you, grows with you.

Your personal AI assistant — easy to install, deploy locally or in the cloud, connect across channels, extend with ease.

Core capabilities:

Under your control — Memory and personalization fully under your control. Deploy locally (data stays on your machine) or in the cloud (your chosen server). No third-party hosting, no data upload.

Skills extension — Built-in scheduling, PDF/Office processing, news digest, and more; custom skills auto-loaded, no lock-in. Skills determine what CoPaw can do.

Multi-agent collaboration — Create multiple independent agents, each with their own role; enable collaboration skills for inter-agent communication to tackle complex tasks together.

Multi-layer security — Tool guard, file access control, skill security scanning to ensure safe operation.

Every channel — DingTalk, Feishu, WeChat, Discord, Telegram, and more. One CoPaw, connect as needed.

What you can do with CoPaw

Social media: Daily hot post digests (Xiaohongshu, Zhihu, Reddit), Bilibili/YouTube video summaries.

Productivity: Email & newsletter highlights pushed to DingTalk/Feishu/QQ; email & calendar contact organization.

Creative & building: Describe your goal before sleep, auto-execute, wake up to a prototype; full workflow from topic selection to final video.

Research & learning: Track tech & AI news, personal knowledge base search and reuse.

Desktop & files: Organize and search local files, read & summarize documents, request files in chat.

Explore more: Combine Skills with scheduled tasks into your own agentic app.

News

[2026-03-24] We released v0.2.0! See the v0.2.0 Release Notes for the full changelog.

[v0.2.0] Added: Inter-agent communication; built-in QA agent; LLM auto-retry settings; file access guard for sensitive paths; audio, video & speech input in console chat; stream reconnection on page refresh; model provider search; multimodal capability probing with UI tags; enhanced grep & glob search; config auto-repair; summarization improvements.
[v0.2.0] Changed: Stable prompts for better KV cache hit rates; faster CLI startup; QQ channel refactor; smart text chunking for QQ & WeCom; QQ WebSocket reconnect config; dark mode polish across console UI.
[v0.2.0] Fixed: Shell command hang on Windows; Windows file path handling; macOS desktop build; channel message processing lock leak; agent list crash and refresh; console reconnect overflow; cron job cancellation.
[v0.2.0] Contributors: Thanks to new contributors: @ixiadao, @leoleils, @ltzu929, @emoubarak, @f3125472, @shiweijiezero, @Yaohua-Leo, @finenter-molei, @lizeruicq, @hbsjmsjwj, @aquamarine-bot, @sanfran1068, @x1n95c, @saschabuehrle.

[2026-03-18] We released v0.1.0! See the v0.1.0 Release Notes for the full changelog.

[2026-03-12] We released v0.0.7! See the v0.0.7 Release Notes for the full changelog.

[2026-03-09] We released v0.0.6! See the v0.0.6 Release Notes for the full changelog.

[2026-03-06] We released v0.0.5! See the v0.0.5 Release Notes for the full changelog.

[2026-03-02] We released v0.0.4! See the v0.0.4 Release Notes for the full changelog.

Recommended reading:

🚀 I'm new and want to try quickly: Quick Start → three commands to run → Configure model → chat in Console

💬 I want to use in DingTalk/Feishu/WeChat: Complete Quick Start → Configure model → Channel setup

🐍 I don't want to install Python: Desktop app or Script install or ModelScope Studio

💻 I want to use local models (no API key needed): Local Models → download model → start using

🛠️ I want to contribute code or develop new features: Install from source → Contributing

News
Quick Start
API Key
Local Models
Documentation
Security Features
FAQ
Staying ahead
Roadmap
Install from source
Contributing
Why CoPaw?
Built by
License

Quick Start

Script install

No Python setup required, one command installs everything. The script will automatically download uv (Python package manager), create a virtual environment, and install CoPaw with all dependencies (including Node.js and frontend assets). Note: May not work in restricted network environments or corporate firewalls.

macOS / Linux:

curl -fsSL https://copaw.agentscope.io/install.sh | bash

To install with Ollama support:

curl -fsSL https://copaw.agentscope.io/install.sh | bash -s -- --extras ollama

To install with multiple extras (e.g., Ollama + llama.cpp):

curl -fsSL https://copaw.agentscope.io/install.sh | bash -s -- --extras ollama,llamacpp

Windows (CMD):

curl -fsSL https://copaw.agentscope.io/install.bat -o install.bat && install.bat

Windows (PowerShell):

irm https://copaw.agentscope.io/install.ps1 | iex

Note: The installer will automatically check the status of uv. If it is not installed, it will attempt to download and configure it automatically. If the automatic installation fails, please follow the on-screen prompts or execute python -m pip install -U uv, then rerun the installer.

⚠️ Special Notice for Windows Enterprise LTSC Users

If you are using Windows LTSC or an enterprise environment governed by strict security policies, PowerShell may run in Constrained Language Mode, potentially causing the following issue:

If using CMD (.bat): Script executes successfully but fails to write to Path

The script completes file installation. Due to Constrained Language Mode, it cannot automatically update environment variables. Manually configure as follows:

Locate the installation directory:

Check if uv is available: Enter uv --version in CMD. If a version number appears, only configure the CoPaw path. If you receive the prompt 'uv' is not recognized as an internal or external command, operable program or batch file, configure both paths.

uv path (choose one based on installation location; use if uv fails): Typically %USERPROFILE%\.local\bin, %USERPROFILE%\AppData\Local\uv, or the Scripts folder within your Python installation directory

CoPaw path: Typically located at %USERPROFILE%\.copaw\bin.

Manually add to the system's Path environment variable:

Press Win + R, type sysdm.cpl and press Enter to open System Properties.

Click “Advanced” -> “Environment Variables”.

Under “System variables”, locate and select Path, then click “Edit”.

Click “New”, enter both directory paths sequentially, then click OK to save.

If using PowerShell (.ps1): Script execution interrupted

Due to Constrained Language Mode, the script may fail to automatically download uv.

Manually install uv: Refer to the GitHub Release to download uv.exe and place it in %USERPROFILE%\.local\bin or %USERPROFILE%\AppData\Local\uv; or ensure Python is installed and run python -m pip install -U uv.

Configure uv environment variables: Add the uv directory and %USERPROFILE%\.copaw\bin to your system's Path variable.

Re-run the installation: Open a new terminal and execute the installation script again to complete the CoPaw installation.

Configure the CoPaw environment variable: Add %USERPROFILE%\.copaw\bin to your system's Path variable.

Once installed, open a new terminal and run:

copaw init --defaults   # or: copaw init (interactive)
copaw app

Install options

macOS / Linux:

# Install a specific version
curl -fsSL ... | bash -s -- --version 0.0.2

# Install from source (dev/testing)
curl -fsSL ... | bash -s -- --from-source

# Upgrade — just re-run the installer
curl -fsSL ... | bash

# Uninstall
copaw uninstall          # keeps config and data
copaw uninstall --purge  # removes everything

Windows (PowerShell):

# Install a specific version
irm ... | iex; .\install.ps1 -Version 0.0.2

# Install from source (dev/testing)
.\install.ps1 -FromSource

# Upgrade — just re-run the installer
irm ... | iex

# Uninstall
copaw uninstall          # keeps config and data
copaw uninstall --purge  # removes everything

pip install

If you prefer managing Python yourself:

pip install copaw
copaw init --defaults
copaw app

Then open the Console in your browser at http://127.0.0.1:8088/ to configure your model. To chat in DingTalk, Feishu, WeChat, etc., see the Channel setup documentation.

Desktop Application (Beta)

Beta Notice: The desktop application is currently in Beta testing phase with the following known limitations:

Incomplete compatibility testing: Not fully tested across all system versions and hardware configurations

Potential performance issues: Startup time, memory usage, and other performance aspects may need further optimization

Features under development: Some features may be unstable or missing

If you're not comfortable with command-line tools, you can download and use CoPaw's desktop application without manually configuring Python environments or running commands.

Download

Download the desktop app from GitHub Releases:

Windows: CoPaw-Setup-<version>.exe
macOS: CoPaw-<version>-macOS.zip (Apple Silicon recommended)

Features

✅ Zero configuration: Download and double-click to run, no need to install Python or configure environment variables
✅ Cross-platform: Supports Windows 10+ and macOS 14+
✅ Visual interface: Automatically opens browser interface, no need to manually enter addresses
⚠️ Beta stage: Features are continuously being improved, feedback welcome

First Launch

Important: The first launch may take 10-60 seconds (depending on your system configuration). The application needs to initialize the Python environment and load dependencies. Please wait patiently for the browser window to open automatically.

macOS: Bypass System Security Restrictions

When you download the CoPaw macOS app from Releases, macOS may show: "Apple cannot verify that 'CoPaw' contains no malicious software". This happens because the app is not notarized. You can still open it as follows:

Right-click to open (recommended) Right-click (or Control+click) the CoPaw app → Open → in the dialog click Open again. This tells Gatekeeper you trust the app; after that you can double-click to launch as usual.
Allow in System Settings If it is still blocked, go to System Settings → Privacy & Security, scroll to the message like "CoPaw was blocked because it is from an unidentified developer", and click Open Anyway or Allow.
Remove quarantine attribute (not recommended for most users) In Terminal run: xattr -cr /Applications/CoPaw.app (or use the path to the .app after unzipping). This clears the "downloaded from the internet" quarantine flag so the warning usually does not appear, but is less safe and controllable than using Right-click → Open.

For detailed usage instructions, troubleshooting, and common issues, see the Desktop Application Guide.

Using ModelScope

No local install? ModelScope Studio one-click cloud setup. Set your Studio to non-public so others cannot control your CoPaw.

Using Docker

Images are on Docker Hub (agentscope/copaw). Image tags: latest (stable); pre (PyPI pre-release).

docker pull agentscope/copaw:latest
docker run -p 127.0.0.1:8088:8088 \
  -v copaw-data:/app/working \
  -v copaw-secrets:/app/working.secret \
  agentscope/copaw:latest

Also available on Alibaba Cloud Container Registry (ACR) for users in China: agentscope-registry.ap-southeast-1.cr.aliyuncs.com/agentscope/copaw (same tags).

Then open http://127.0.0.1:8088/ for the Console. Config, memory, and skills are stored in the copaw-data volume; model provider settings and API keys are in the copaw-secrets volume. To pass API keys (e.g. DASHSCOPE_API_KEY), add -e VAR=value or --env-file .env to docker run.

Connecting to Ollama or other services on the host machine

Inside a Docker container, localhost refers to the container itself, not your host machine. If you run Ollama (or other model services) on the host and want CoPaw in Docker to reach them, use one of these approaches:

Option A — Explicit host binding (all platforms):
docker run -p 127.0.0.1:8088:8088 \
  --add-host=host.docker.internal:host-gateway \
  -v copaw-data:/app/working \
  -v copaw-secrets:/app/working.secret \
  agentscope/copaw:latest
Then in CoPaw Settings → Models, change the Base URL to http://host.docker.internal:<port> — for example, http://host.docker.internal:11434 for Ollama, or http://host.docker.internal:1234/v1 for LM Studio.

Option B — Host networking (Linux only):
docker run --network=host \
  -v copaw-data:/app/working \
  -v copaw-secrets:/app/working.secret \
  agentscope/copaw:latest
No port mapping (-p) is needed; the container shares the host network directly. Note that all container ports are exposed on the host, which may cause conflicts if the port is already in use.

Note: If you only mount /app/working without a separate volume for /app/working.secret, the entrypoint will automatically redirect secrets into /app/working/.secret so they persist on the same volume.

The image is built from scratch. To build the image yourself, please refer to the Build Docker image section in scripts/README.md, and then push to your registry.

Deploy on Alibaba Cloud ECS

To run CoPaw on Alibaba Cloud (ECS), use the one-click deployment: open the CoPaw on Alibaba Cloud (ECS) deployment link and follow the prompts. For step-by-step instructions, see Alibaba Cloud Developer: Deploy your AI assistant in 3 minutes.

API Key

If you use a cloud LLM API (e.g., Qianwen, Gemini, OpenAI), you must configure an API key before chatting. CoPaw will not work until a valid key is set. See the official docs for details.

How to configure:

Console (recommended) — After running copaw app, open http://127.0.0.1:8088/ → Settings → Models. Choose a provider, enter the API Key, and enable that provider and model.
copaw init — When you run copaw init, it will guide you through configuring the LLM provider and API key. Follow the prompts to choose a provider and enter your key.
Environment variable — For DashScope you can set DASHSCOPE_API_KEY in your shell or in a .env file in the working directory.

Tools that need extra keys (e.g. TAVILY_API_KEY for web search) can be set in Console Settings → Environment variables, see Config for details.

Using local models only? If you use Local Models (llama.cpp or MLX), you do not need any API key.

Local Models

CoPaw can run LLMs entirely on your machine — no API keys or cloud services required. See the official docs for details.

Backend	Best for	Install
llama.cpp	Cross-platform (macOS / Linux / Windows)	`pip install 'copaw[llamacpp]'` or `bash install.sh --extras llamacpp`
MLX	Apple Silicon Macs (M1/M2/M3/M4)	`pip install 'copaw[mlx]'` or `bash install.sh --extras mlx`
Ollama	Cross-platform (requires Ollama service)	`pip install 'copaw[ollama]'` or `bash install.sh --extras ollama`

After installing, you can download and manage local models in the Console UI. You can also use the command line:

copaw models download Qwen/Qwen3-4B-GGUF
copaw models # select the downloaded model
copaw app # start the server

Documentation

Topic	Description
Introduction	What CoPaw is and how to use it
Quick start	Install and run (local or ModelScope Studio)
Console	Web UI: chat and agent configuration
Models	Configure cloud, local, and custom providers
Channels	DingTalk, Feishu, QQ, Discord, iMessage, and more
Skills	Extend and customize capabilities
MCP	Manage MCP clients
Memory	Long-term memory
Context	Context management mechanism
Magic commands	Control conversation state without waiting for the AI
Heartbeat	Scheduled check-in and digest
Multi-Agent	Create multiple agents and enable collaboration
Config & working dir	Working directory and config file
CLI	Init, cron jobs, skills, clean
FAQ	Common questions and troubleshooting

Full docs in this repo: website/public/docs/.

Security Features

CoPaw includes multi-layer security mechanisms to protect your data and system:

Tool guard — Automatically intercepts dangerous shell commands (e.g., rm -rf /, fork bombs, reverse shells, etc.)
File access guard — Restricts agent access to sensitive paths (e.g., ~/.ssh, key files, system directories, etc.)
Skill security scanning — Automatically scans before installing skills, detecting risks like prompt injection, command injection, hardcoded keys, data exfiltration, etc.
Local deployment — All data and memory stored locally, no third-party upload (when using cloud LLM APIs, conversation content is sent to the corresponding API provider)

See Security documentation for details.

FAQ

For common questions, troubleshooting tips, and known issues, please visit the FAQ page.

Staying ahead

Star CoPaw on GitHub and be instantly notified of new releases.

Roadmap

Area	Item	Status
Horizontal Expansion	More channels, models, skills, MCPs — community contributions welcome	Seeking Contributors
Existing Feature Extension	Display optimization, download hints, Windows path compatibility, etc. — community contributions welcome	Seeking Contributors
Console Web UI	Expose more info/config in the Console	In Progress
Self-healing	DaemonAgent: autonomous diagnostics, self-healing, and recovery	In Progress
Multi-agent	Background task support	In Progress
	Async tasks	Planned
	Inter-agent contention resolution	Planned
Multimodal	Voice/video calls and real-time interaction	In Progress
Small + Large Model Collaboration	Train/fine-tune local small LLMs for CoPaw workflows	In Progress
	Multi-model routing; different models for different tasks	In Progress
Memory System	Experience distillation & skill extraction	In Progress
	Memory mechanism switching	Planned
	Multimodal memory fusion	Planned
	Context-aware proactive delivery	Planned
Sandbox	Deeper integration with AgentScope Runtime sandboxes	In Progress
Cloud-native	Deeper integration with AgentScope Runtime; leverage cloud compute, storage, and tooling	Planned
Skills Hub	Enrich the AgentScope Skills repository and improve discoverability of high-quality skills	Planned

Status: In Progress — actively being worked on; Planned — queued or under design, also welcome contributions; Seeking Contributors — we strongly encourage community contributions.

Install from source

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

# Build console frontend first (required for web UI)
cd console && npm ci && npm run build
cd ..

# Copy console build output to package directory
mkdir -p src/copaw/console
cp -R console/dist/. src/copaw/console/

# Install Python package
pip install -e .

Dev (tests, formatting): pip install -e ".[dev,full]"
Then: Run copaw init --defaults, then copaw app.

Note for updates: When updating to a new major version after git pull, please also rebuild the frontend, reinstall the package (pip install -e .), restart copaw app, and clear your browser cache with Ctrl+Shift+R (or Cmd+Shift+R on macOS).

Contributing

CoPaw evolves through open collaboration, and we welcome all forms of contribution! Check the Roadmap above (especially items marked Seeking Contributors) to find areas that interest you, and read CONTRIBUTING to get started. We particularly welcome:

Horizontal expansion — new channels, model providers, skills, MCPs.
Existing feature extension & refinement — display and interaction improvements, download hints, Windows path compatibility, etc.

Join GitHub Discussions to discuss ideas or pick up tasks.

Why CoPaw?

CoPaw represents both a Co Personal Agent Workstation and a "co-paw"—a partner always by your side. More than just a cold tool, CoPaw is a warm "little paw" always ready to lend a hand (or a paw!). It is the ultimate teammate for your digital life.

Built by

AgentScope team · AgentScope · AgentScope Runtime · ReMe

Contact us

Discord	X (Twitter)	DingTalk

Telemetry

CoPaw collects anonymous usage data during copaw init to help us understand our user base and prioritize improvements. Data is sent once per version — when you upgrade CoPaw, telemetry is re-collected so we can track version adoption.

What we collect:

CoPaw version (e.g., 0.0.7)
Install method (pip, Docker, or desktop app)
OS and version (e.g., macOS 14.0, Ubuntu 22.04)
Python version (e.g., 3.13)
CPU architecture (e.g., x86_64, arm64)
GPU availability (yes/no)

What we do NOT collect: No personal data, no files, no credentials, no IP addresses, no identifiable information.

When running copaw init interactively, you will be asked whether to opt in. If you choose --defaults, telemetry is accepted automatically. The prompt appears once per version and never affects CoPaw's functionality.

License

CoPaw is released under the Apache License 2.0.

Contributors

All thanks to our contributors:

Name		Name	Last commit message	Last commit date
Latest commit History 580 Commits
.github		.github
console		console
deploy		deploy
scripts		scripts
src/copaw		src/copaw
tests		tests
website		website
.dockerignore		.dockerignore
.flake8		.flake8
.gitattributes		.gitattributes
.gitignore		.gitignore
.pre-commit-config.yaml		.pre-commit-config.yaml
.python-version		.python-version
CONTRIBUTING.md		CONTRIBUTING.md
CONTRIBUTING_zh.md		CONTRIBUTING_zh.md
LICENSE		LICENSE
README.md		README.md
README_ja.md		README_ja.md
README_ru.md		README_ru.md
README_zh.md		README_zh.md
SECURITY.md		SECURITY.md
docker-compose.yml		docker-compose.yml
package-lock.json		package-lock.json
pyproject.toml		pyproject.toml
setup.py		setup.py

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CoPaw

News

Table of Contents

Quick Start

Script install

pip install

Desktop Application (Beta)

Download

Features

First Launch

macOS: Bypass System Security Restrictions

Using ModelScope

Using Docker

Deploy on Alibaba Cloud ECS

API Key

Local Models

Documentation

Security Features

FAQ

Staying ahead

Roadmap

Install from source

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Repository files navigation

CoPaw

News

Table of Contents

Quick Start

Script install

pip install

Desktop Application (Beta)

Download

Features

First Launch

macOS: Bypass System Security Restrictions

Using ModelScope

Using Docker

Deploy on Alibaba Cloud ECS

API Key

Local Models

Documentation

Security Features

FAQ

Staying ahead

Roadmap

Install from source

Contributing

Why CoPaw?

Built by

Contact us

Telemetry

License

Contributors

About

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Contributing

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