MCP et appels d’outils

QwenPaw

agentscope-ai/qwenpaw

A self-hostable personal AI assistant that runs locally or in the cloud, featuring multi-channel connectivity, extensible skills, and a three-layer memory system.

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⑂ 3KForks
947Problèmes ouverts
PythonLangue
Apache-2.0Licence
Q@project.QualityScoreScore éditorial

Captures d'écran du projet

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Vue d’ensemble

QwenPaw is an open-source personal AI assistant developed by agentscope-ai. Built on the AgentScope 2.0 architecture, it provides an Agent OS environment that manages resources, governance, and sandboxing for autonomous agents. It supports local execution via QwenPaw-Flash models or integration with over 14 cloud providers. The system is designed to be reachable across various messaging platforms and offers a unified file workspace, multi-agent orchestration, and continuous memory evolution.

Fonctionnalités clés

  • Three-layer memory with self-evolving personal knowledge base (ReMe)
  • Local or cloud deployment with no mandatory API keys
  • Kernel-level Sandbox, Tool Guard, File Guard, Skill Scanner, and Access Policy
  • Multi-agent and parallel execution with Agent Communication Protocol (ACP)
  • Unified file workspace with navigation, preview, editing, and diffs
  • Extensible Skills and Plugin architecture with marketplace and MCP integration
  • Multi-channel connectivity (DingTalk, Lark, WeChat, Discord, Telegram, iMessage, QQ)
  • Console, Terminal UI (TUI), and desktop application interfaces
  • Scroll Context for full conversation persistence without summarization

Prérequis, installation et démarrage rapide

Multiple installation methods are supported: 1) Pip install: `pip install qwenpaw`, then `qwenpaw init --defaults`, then `qwenpaw app`. 2) Script install for macOS/Linux: `curl -fsSL https://qwenpaw.agentscope.io/install.sh | bash`. 3) Script install for Windows (PowerShell): `irm https://qwenpaw.agentscope.io/install.ps1 | iex`. 4) Docker: `docker pull agentscope/qwenpaw:latest` followed by `docker run -p 127.0.0.1:8088:8088 -v qwenpaw-data:/app/working -v qwenpaw-secrets:/app/working.secret -v qwenpaw-backups:/app/working.backups agentscope/qwenpaw:latest`. 5) Desktop Application (Beta) available for Windows 10+ and macOS 14+. 6) Cloud deployment options available via Alibaba Cloud ECS, AgentScope Platform, and ModelScope Studio.

Utilisation

After installation, run `qwenpaw app` and open the Console at http://127.0.0.1:8088/ to configure models. For terminal users, run `qwenpaw` to open the TUI, `qwenpaw tui --resume <id>` to resume a session, or `qwenpaw .` to start in Coding Mode. API keys for cloud providers can be configured in Console under Settings -> Models, via `qwenpaw init`, or through environment variables.

Compatibilité des modèles et cas d’usage

Supports QwenPaw-Flash series models (2B, 4B, 9B with Q4 and Q8 quantizations) via the built-in QwenPaw Local runtime. Also compatible with Ollama, LM Studio, and cloud providers including DashScope/Qwen, OpenAI, Anthropic, Google Gemini, DeepSeek, Kimi, and OpenRouter.

Licence et notes sur les risques

Licensed under the Apache-2.0 license.

Editorial verification 2026-08-09: repository URL, owner, description, license and repository statistics were reviewed. License metadata: Apache-2.0. README was fetched for the channel draft; re-check repository dependencies, releases and model terms before production use.

Publication et maintenance

v2.0.1 (2026-07-24) introduced PawApp mini-app platform, user-editable Agent Modes, Oh-My-Paw plugins, and ReMe memory enhancements. v2.0.0 (2026-07-10) was a ground-up rewrite based on AgentScope 2.0, delivering Agent OS architecture, Loop Engineering, Scroll Context, ReMe v0.4, and a Terminal UI. v1.1.12 (2026-06-17) overhauled the Models page and added Simple Mode. v1.1.11 (2026-06-10) added Free Model OAuth, Plugin Market, and MCP Tool Whitelisting.

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