WeCom Bot MCP Server

# WeCom Bot MCP Server <div align="center"> <img src="wecom.png" alt="WeCom Bot Logo" width="200"/> </div> A Model Context Protocol (MCP) compliant server implementation for WeCom (WeChat Work) bot. [](https://badge.fury.io/py/wecom-bot-mcp-server) [](https://pypi.org/project/wecom-bot-mcp-server/) [](https://app.codecov.io/gh/loonghao/wecom-bot-mcp-server) [](https://github.com/astral-sh/ruff) [](https://smithery.ai/server/wecom-bot-mcp-server) [English](README.md) | [中文](README_zh.md) <a href="https://glama.ai/mcp/servers/amr2j23lbk"><img width="380" height="200" src="https://glama.ai/mcp/servers/amr2j23lbk/badge" alt="WeCom Bot Server MCP server" /></a> ## Features - Support for multiple message types: - Text messages - Markdown messages - Image messages (base64) - File messages - @mention support (via user ID or phone number) - Message history tracking - Configurable logging system - Full type annotations - Pydantic-based data validation ## Requirements - Python 3.10+ - WeCom Bot Webhook URL (obtained from WeCom group settings) ## Installation There are several ways to install WeCom Bot MCP Server: ### 1. Automated Installation (Recommended) #### Using Smithery (For Claude Desktop): ```bash npx -y @smithery/cli install wecom-bot-mcp-server --client claude ``` #### Using VSCode with Cline Extension: 1. Install [Cline Extension](https://marketplace.visualstudio.com/items?itemName=saoudrizwan.claude-dev) from VSCode marketplace 2. Open Command Palette (Ctrl+Shift+P / Cmd+Shift+P) 3. Search for "Cline: Install Package" 4. Type "wecom-bot-mcp-server" and press Enter ### 2. Manual Installation #### Install from PyPI: ```bash pip install wecom-bot-mcp-server ``` #### Configure MCP manually: Create or update your MCP configuration file: ```json // For Windsurf: ~/.windsurf/config.json { "mcpServers": { "wecom": { "command": "uvx", "args": [ "wecom-bot-mcp-server" ], "env": { "WECOM_WEBHOOK_URL": "your-webhook-url" } } } } ``` ## Configuration ### Setting Environment Variables ```bash # Windows PowerShell $env:WECOM_WEBHOOK_URL = "your-webhook-url" # Optional configurations $env:MCP_LOG_LEVEL = "DEBUG" # Log levels: DEBUG, INFO, WARNING, ERROR, CRITICAL $env:MCP_LOG_FILE = "path/to/custom/log/file.log" # Custom log file path ``` ### Log Management The logging system uses `platformdirs.user_log_dir()` for cross-platform log file management: - Windows: `C:\Users\<username>\AppData\Local\hal\wecom-bot-mcp-server` - Linux: `~/.local/share/hal/wecom-bot-mcp-server` - macOS: `~/Library/Application Support/hal/wecom-bot-mcp-server` The log file is named `mcp_wecom.log` and is stored in the above directory. ## Usage ### Starting the Server ```bash wecom-bot-mcp-server ``` ### Usage Examples (With MCP) ```python # Scenario 1: Send weather information to WeCom USER: "How's the weather in Shenzhen today? Send it to WeCom" ASSISTANT: "I'll check Shenzhen's weather and send it to WeCom" await mcp.send_message( content="Shenzhen Weather:\n- Temperature: 25°C\n- Weather: Sunny\n- Air Quality: Good", msg_type="markdown" ) # Scenario 2: Send meeting reminder and @mention relevant people USER: "Send a reminder for the 3 PM project review meeting, remind Zhang San and Li Si to attend" ASSISTANT: "I'll send the meeting reminder" await mcp.send_message( content="## Project Review Meeting Reminder\n\nTime: Today 3:00 PM\nLocation: Meeting Room A\n\nPlease be on time!", msg_type="markdown", mentioned_list=["zhangsan", "lisi"] ) # Scenario 3: Send a file USER: "Send this weekly report to the WeCom group" ASSISTANT: "I'll send the weekly report" await mcp.send_message( content=Path("weekly_report.docx"), msg_type="file" ) ``` ### Direct API Usage #### Send Messages ```python from wecom_bot_mcp_server import mcp # Send markdown message await mcp.send_message( content="**Hello World!**", msg_type="markdown" ) # Send text message and mention users await mcp.send_message( content="Hello @user1 @user2", msg_type="text", mentioned_list=["user1", "user2"] ) ``` #### Send Files ```python from wecom_bot_mcp_server import send_wecom_file # Send file await send_wecom_file("/path/to/file.txt") ``` #### Send Images ```python from wecom_bot_mcp_server import send_wecom_image # Send local image await send_wecom_image("/path/to/image.png") # Send URL image await send_wecom_image("https://example.com/image.png") ``` ## Development ### Setup Development Environment 1. Clone the repository: ```bash git clone https://github.com/loonghao/wecom-bot-mcp-server.git cd wecom-bot-mcp-server ``` 2. Create a virtual environment and install dependencies: ```bash # Using uv (recommended) pip install uv uv venv uv pip install -e ".[dev]" # Or using traditional method python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -e ".[dev]" ``` ### Testing ```bash # Using uv (recommended) uvx nox -s pytest # Or using traditional method nox -s pytest ``` ### Code Style ```bash # Check code uvx nox -s lint # Automatically fix code style issues uvx nox -s lint_fix ``` ### Building and Publishing ```bash # Build the package uv build # Build and publish to PyPI uv build && twine upload dist/* ``` ## Project Structure ``` wecom-bot-mcp-server/ ├── src/ │ └── wecom_bot_mcp_server/ │ ├── __init__.py │ ├── server.py │ ├── message.py │ ├── file.py │ ├── image.py │ ├── utils.py │ └── errors.py ├── tests/ │ ├── test_server.py │ ├── test_message.py │ ├── test_file.py │ └── test_image.py ├── docs/ ├── pyproject.toml ├── noxfile.py └── README.md ``` ## License This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. ## Contact - Author: longhao - Email: hal.long@outlook.com