MCP Server for WeChat — let AI read and send WeChat messages
Project description
WeChat MCP Server
让 AI 读写微信消息 — 通过 Model Context Protocol (MCP) 标准协议,AI 助手可以直接搜索联系人、读取聊天、发送消息。
AI agents can read and write WeChat messages through the Model Context Protocol (MCP).
✨ 功能 Features
| 功能 | 说明 |
|---|---|
| 📥 读聊天 | 截取聊天窗口 → Qwen-VL 识别文字 → 返回结构化消息 |
| 📤 发消息 | 搜索联系人 → 截图验证 → 粘贴发送 |
| 🔍 搜联系人 | Cmd+F 搜索 → 自动验证是否打开正确聊天 |
| 🟡 红点检测 | OpenCV 检测未读消息红点位置 |
| 👁️ 视觉分析 | 使用阿里云 DashScope Qwen-VL-Plus 理解截图内容 |
📋 需求 Requirements
- macOS (WeChat for Mac)
- Python 3.10+
- WeChat 已登录且主窗口可见
- cua-driver — 快捷键自动化层(GitHub)
- DashScope API Key — 阿里云百炼视觉模型(免费额度)
🚀 快速开始 Quick Start
1. 安装
pip install wechat-mcp
或者从源码安装:
git clone https://github.com/jp7454yv4f-sudo/WeChat-mcp.git
cd WeChat-mcp
pip install -e .
2. 配置 API Key
# 方式一:环境变量(推荐)
export WEIXIN_MCP_API_KEY='sk-...'
# 方式二:配置文件
# 创建 ~/.wechat_mcp/config.json:
# {"dashscope_api_key": "sk-..."}
API Key 获取:https://dashscope.aliyun.com → 模型广场 → Qwen-VL-Plus
3. 启动
wechat-mcp
4. 配置 MCP 客户端
Claude Desktop:
{
"mcpServers": {
"wechat": {
"command": "wechat-mcp"
}
}
}
Cursor / Windsurf:
MCP Server → Add → Command: wechat-mcp
🛠️ 可用工具 Available Tools
| 工具 | 参数 | 说明 |
|---|---|---|
search_contact |
name |
搜索并打开联系人聊天 |
send_message |
contact, text |
发送消息(自动验证) |
read_chat |
contact? |
读取当前/指定聊天内容 |
reply_message |
contact, text |
发送消息 + 语气迭代记录 |
list_contacts |
— | 列出所有有过对话的联系人 |
detect_new_messages |
interval_seconds |
红点检测循环 |
🔧 技术栈 Tech Stack
| 组件 | 技术 |
|---|---|
| 协议 | Model Context Protocol (MCP) |
| 自动化驱动 | cua-driver / osascript 快捷键 |
| 截图 | macOS screencapture |
| 红点检测 | OpenCV HSV 颜色空间 |
| 视觉理解 | Qwen-VL-Plus (DashScope) |
💰 运营成本
每次 API 调用约 0.002元(Qwen-VL-Plus),完整读写一次约 0.01元。 红点检测为本地 OpenCV,零成本。
📄 许可 License
GNU AGPL v3 — 开源但保护作者权益。
- ✅ 个人/内部使用免费
- ✅ 修改后自用免费
- ❌ 修改后作为 SaaS/网络服务提供须开源修改内容
- ❌ 闭源的商业分发需要授权
商业授权请联系:jp7454yv4f-sudo@users.noreply.github.com
🧑💻 作者 Author
Lozzi — built for AI-powered WeChat automation.
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