WeClaw: A Personal Assistant Powered by Mobile QQ and Windows PC Collaboration

中文 README

A cross-platform personal assistant agent inspired by OpenClaw, designed for Windows PCs. It bridges mobile QQ and Windows capabilities so users can use natural language to plan and execute tasks end-to-end across devices.

WeClaw can also be accessed via a CLI, and can be customized to integrate with platforms such as WhatsApp, Discord, Telegram, and more.

GUI Preview

Timeline

• 2026-02-03 🎉 WeClaw is now open source.
• 2026-02-23 🖥️ Added a graphical Agent Console (angel_console/) for unified operations:
  • Chat (SSE streaming + ReAct trace)
  • Voice input (browser recording + local transcription)
  • Search tasks (session retrieval and context navigation)
  • Channels (Web / CLI / QQ / Discord)
  • Scheduled tasks (Cron) and heartbeat
  • Skills management
  • Model configuration and switching
  • Model billing and call audit (token statistics)
• 2026-03-07 🔌 Added an integrated MCP stack:
  • Local and remote MCP client runtime
  • Web Console MCP discovery, configuration, and runtime management
• 2026-03-09 🚪 Unified the project startup flow around the Web Console:
  • Added entry_console.py as the recommended root entrypoint
  • Added python -m angel_console package startup

Core Highlights

• Cross-platform personal agent: mobile QQ ↔ Windows PC collaboration
• Multi-agent architecture: parallel decomposition and execution for complex tasks
• Intelligent routing: choose ReAct or ReCAP based on task complexity
• Context engineering: compression, unloading, and filesystem support to avoid context overflow
• Secure sandbox and async execution: more stable long-running task pipelines
• Skills integration: unified mechanism supporting customization and extension
• Task state management: supports long-chain, multi-turn task automation
• Stable execution strategy: plan first, then act
• Experience learning is being integrated: improves with usage

Demo GIFs

🔎 Information Gathering & Report Generation	⏰ Scheduled Tasks & Automation	🧩 Automatic Skills Creation	💻 Coding & Remote Execution

Capability Overview

• Information gathering and organization
• Report and document generation
• Scheduled tasks and automation
• Cross-device development and execution of coding tasks

Graphical Agent Console

The project now includes a local graphical control plane in angel_console/ to manage core agent capabilities in one place.
By default, the console binds to 127.0.0.1 and is intended for local development and operations.

Main modules:

• Chat: session management, streaming responses, and tool trace visualization
• Voice Input: browser-side recording with local speech-to-text (Chinese and English)
• Search Tasks: cross-session retrieval with fast jump to relevant context
• Channels: unified channel configuration and status for Web / CLI / QQ / Discord
• Cron & Heartbeat: periodic jobs, manual triggers, and runtime status controls
• Skills: discover and manage available skills from the workspace
• Models: configure multiple providers/profiles and switch active runtime model
• Model Billing: inspect call volume, token usage, failure rate, and call-level details

Recommended Startup

The Web Console is now the recommended primary entrypoint for the project.

python entry_console.py

Alternative package-style startup:

python -m angel_console

Then open http://127.0.0.1:7788 in your browser.

Recommended workflow: start from the Web Console first, then use the Channels page to manage CLI / QQ / Discord.

Direct channel scripts are still supported for advanced use:

python channels/cli.py
python channels/qq.py
python channels/discord.py

Legacy compatibility wrappers are also still available:

python entry_cli.py
python entry_qq.py
python entry_discord.py

Use Cases

You can direct the agent anytime, anywhere (on the subway, while traveling, or on your bed):

• Fast collection and structured organization of work/study materials
• Automatic generation of reports, checklists, and summaries
• Multi-step tasks that require cross-device collaboration
• Personal development workflows and script-based automation

Prerequisites

Environment variables:

• LLM_API_KEY (required, for model calls)
• LLM_BASE_URL (optional; defaults are chosen by LLM_PROVIDER)
• LLM_MODEL (optional; defaults are chosen by LLM_PROVIDER)
• LLM_PROVIDER (optional, openai|anthropic|dashscope; can be auto-detected)
• BRAVE_API_KEY (optional, for web search)
• ZHIPU_API_KEY (optional, for web search)
• BOTPY_APPID (required, for QQ entry)
• BOTPY_SECRET (required, for QQ entry)
• LITTLE_ANGEL_AGENT_WORKSPACE (optional, workspace path for the agent)

Local Secrets File

Create local_secrets.yaml in the project root and fill in your keys:

LLM_API_KEY: ""
LLM_BASE_URL: ""
LLM_MODEL: ""
LLM_PROVIDER: ""
ZHIPU_API_KEY: ""
BOTPY_APPID: ""
BOTPY_SECRET: ""

Note: Get the QQ bot APPID and SECRET by registering on Tencent QQ Open Platform and creating a bot: https://q.qq.com/#/

Run

Web Console (Recommended)

python entry_console.py

Or:

python -m angel_console

Open http://127.0.0.1:7788 after startup.

CLI

python entry_cli.py

Direct channel path:

python channels/cli.py

QQ Direct Message

python entry_qq.py

Direct channel path:

python channels/qq.py

Discord

python entry_discord.py

Direct channel path:

python channels/discord.py

Project Structure

• entry_qq.py: QQ direct message entry
• entry_cli.py: CLI entry
• little_angel_bot.py: core bot logic
• tools/: tool capabilities
• skills/: Skills integration

Additional entrypoint files introduced for the Web Console workflow:

• entry_console.py: unified root entry for the browser console
• channels/: direct channel entrypoints for CLI / QQ / Discord

Development and Extension

• Add or modify skills in skills/
• Add new tool capabilities in tools/
• Customize behavior through the unified Skills mechanism

License

MIT