QwenPaw
Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
QwenPaw is a personal AI assistant agent that developers can deploy locally or in the cloud, featuring extensible capabilities through skills, plugins, and MCP integration. Built on AgentScope 2.0, it provides a three-layer memory system (working context, full history, and self-evolving knowledge base powered by ReMe), supports multiple chat platforms (DingTalk, Lark, Discord, Telegram, iMessage), and includes kernel-level security sandboxing. The agent can run entirely offline with local models (QwenPaw-Flash 2B/4B/9B, Ollama, LM Studio) or connect to 14+ cloud LLM providers, making it suitable for developers who need a customizable AI assistant with strong privacy guarantees.
Key Features
Use Cases
- 01Automated scheduling and recurring tasks like news digests, report generation, and multi-channel broadcasting
- 02Code development with project file reading, editing, review, and testing through the unified workspace
- 03Document processing and conversion for PDF, Word, Excel, and PowerPoint files
- 04Information gathering via web search, RSS subscriptions, video summarization, and personal knowledge base queries
- 05Multi-channel operations pushing AI-generated alerts and summaries to team communication platforms simultaneously
- 06Privacy-focused AI assistance with all data and processing kept on-premises using local LLMs
Related Agents
View morehermes-agent
The agent that grows with you
agency-agents
A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers. Each agent is a specialized expert with personality, processes, and proven deliverables.
openinterpreter
A coding agent for open models like Kimi K3
cline
Autonomous coding agent as an SDK, IDE extension, or CLI assistant.
QwenPaw — FAQ
What is QwenPaw?+
QwenPaw is a personal AI assistant agent that can be deployed locally or in the cloud, with extensible skills, multi-channel support, and a self-evolving memory system. It functions as a complete AI workstation with security sandboxing and multi-agent collaboration capabilities.
How do I install QwenPaw?+
Install via pip with 'pip install qwenpaw && qwenpaw init --defaults && qwenpaw app', use the one-line script installer for automatic setup, deploy with Docker using the agentscope/qwenpaw image, or download the desktop application for Windows or macOS. Python 3.11 to <3.14 is required for pip installation.
Do I need API keys to use QwenPaw?+
No API keys are required if you use local models like QwenPaw-Flash, Ollama, or LM Studio. If you choose cloud LLM providers (DashScope/Qwen, OpenAI, Anthropic, Google Gemini, DeepSeek), you must configure an API key in Settings → Models or via environment variables.
Which AI clients does QwenPaw work with?+
QwenPaw is a standalone agent system accessed through its Console web UI (port 8088), Terminal UI (TUI), desktop app, or REST API. It integrates with chat platforms like DingTalk, Lark, Discord, and Telegram as communication channels, not as a plugin for other AI clients.
Is QwenPaw free to use?+
Yes, QwenPaw is open-source under Apache 2.0 license and free to use. Cloud LLM API usage incurs costs from the respective providers, but local model operation (QwenPaw-Flash, Ollama, LM Studio) has no ongoing fees.
What are the system requirements?+
Python 3.11 to <3.14 for pip installation; Docker for container deployment; macOS 14+, Windows 10+, or Linux for the desktop app. For local models, sufficient RAM and GPU (optional but recommended) are needed depending on model size.
How do I install QwenPaw?+
Open the source repository on GitHub and follow its README. QwenPaw is a agent — MCP Agents Market links you directly to the official repo.
Is QwenPaw free?+
QwenPaw is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.