WeCom Bot MCP Server

[](https://mseep.ai/app/loonghao-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: - Markdown messages (with @mentions and font colors) - Markdown V2 messages (with tables, lists, embedded images) - Image messages (base64/local file/URL) - File messages - Template card messages (text_notice and news_notice) - **Multi-bot support**: Configure and use multiple WeCom bots - @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 Configuration Add the server to your MCP client configuration file: ```json // For Claude Desktop on macOS: ~/Library/Application Support/Claude/claude_desktop_config.json // For Claude Desktop on Windows: %APPDATA%\Claude\claude_desktop_config.json // For Windsurf: ~/.windsurf/config.json // For Cline in VSCode: VSCode Settings > Cline > MCP Settings { "mcpServers": { "wecom": { "command": "uvx", "args": [ "wecom-bot-mcp-server" ], "env": { "WECOM_WEBHOOK_URL": "your-webhook-url" } } } } ``` ## Configuration ### Setting Environment Variables #### Single Bot (Default) ```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 ``` #### Multiple Bots Configuration You can configure multiple bots using any of these methods: **Method 1: JSON Configuration (Recommended)** ```bash # Windows PowerShell $env:WECOM_BOTS = '{"alert": {"name": "Alert Bot", "webhook_url": "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=xxx", "description": "For alerts"}, "ci": {"name": "CI Bot", "webhook_url": "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=yyy", "description": "For CI/CD"}}' # Linux/macOS export WECOM_BOTS='{"alert": {"name": "Alert Bot", "webhook_url": "https://...", "description": "For alerts"}, "ci": {"name": "CI Bot", "webhook_url": "https://...", "description": "For CI/CD"}}' ``` **Method 2: Individual Environment Variables** ```bash # Windows PowerShell $env:WECOM_BOT_ALERT_URL = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=xxx" $env:WECOM_BOT_CI_URL = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=yyy" $env:WECOM_BOT_NOTIFY_URL = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=zzz" ``` **Method 3: Combined Mode** ```bash # WECOM_WEBHOOK_URL becomes the "default" bot $env:WECOM_WEBHOOK_URL = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=default" # Additional bots $env:WECOM_BOT_ALERT_URL = "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=alert" ``` #### MCP Client Configuration with Multiple Bots ```json { "mcpServers": { "wecom": { "command": "uvx", "args": ["wecom-bot-mcp-server"], "env": { "WECOM_WEBHOOK_URL": "https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=default", "WECOM_BOTS": "{\"alert\": {\"name\": \"Alert Bot\", \"webhook_url\": \"https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=alert\"}, \"ci\": {\"name\": \"CI Bot\", \"webhook_url\": \"https://qyapi.weixin.qq.com/cgi-bin/webhook/send?key=ci\"}}" } } } } ``` ### 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\Logs` - Linux: `~/.local/state/hal/wecom-bot-mcp-server/log` - macOS: `~/Library/Logs/hal/wecom-bot-mcp-server` The log file is named `mcp_wecom.log` and is stored in the above directory. You can customize the log level and file path using environment variables: - `MCP_LOG_LEVEL`: Set to DEBUG, INFO, WARNING, ERROR, or CRITICAL - `MCP_LOG_FILE`: Set to a custom log file path ## Usage Once configured, the MCP server runs automatically when your MCP client starts. You can interact with it through natural language in your AI assistant. ### Usage Examples **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" [The assistant will use the send_message tool to send the weather information] ``` **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" [The assistant will use the send_message tool with mentioned_list parameter] ``` **Scenario 3: Send a file** ``` USER: "Send this weekly report to the WeCom group" ASSISTANT: "I'll send the weekly report" [The assistant will use the send_file tool] ``` **Scenario 4: Send an image** ``` USER: "Send this chart image to WeCom" ASSISTANT: "I'll send the image" [The assistant will use the send_image tool] ``` ### Available MCP Tools The server provides the following tools that your AI assistant can use: 1. **send_message** - Send text or markdown messages - Parameters: `content`, `msg_type` (markdown/markdown_v2), `mentioned_list`, `mentioned_mobile_list`, `bot_id` - `markdown`: Use when content contains `<@userid>` mentions or font colors. The `<@userid>` syntax is WeCom's official mention format, which avoids conflicts with email addresses like `@user@email.com` - `markdown_v2`: Use for tables, lists, embedded images, or general content (default) 2. **send_wecom_file** - Send files to WeCom - Parameters: `file_path`, `bot_id` 3. **send_wecom_image** - Send images to WeCom - Parameters: `image_path` (local path or URL), `bot_id` 4. **send_wecom_template_card_text_notice** - Send text notice template card - Parameters: `template_card_source`, `template_card_main_title`, `template_card_card_action`, `bot_id`, and optional fields - Use for notifications with emphasis content, quotes, and action buttons 5. **send_wecom_template_card_news_notice** - Send news notice template card - Parameters: `template_card_source`, `template_card_main_title`, `template_card_card_action`, `template_card_image`, `bot_id`, and optional fields - Use for news-style notifications with images and rich content 6. **list_wecom_bots** - List all configured bots - Returns: List of available bots with their IDs, names, and descriptions ### Multi-Bot Usage Examples **Scenario 5: Send alert to specific bot** ``` USER: "Send a critical alert to the alert bot: Server CPU usage is above 90%" ASSISTANT: "I'll send the alert to the alert bot" [The assistant will use send_message with bot_id="alert"] ``` **Scenario 6: List available bots** ``` USER: "What WeCom bots are available?" ASSISTANT: "Let me check the available bots" [The assistant will use list_wecom_bots tool] ``` **Scenario 7: Send CI notification** ``` USER: "Send build success notification to the CI bot" ASSISTANT: "I'll send the notification to the CI bot" [The assistant will use send_message with bot_id="ci"] ``` **Scenario 8: Send template card notification** ``` USER: "Send a deployment success notification card with a link to the dashboard" ASSISTANT: "I'll send a template card notification" [The assistant will use send_wecom_template_card_text_notice tool] ``` **Scenario 9: Send news-style notification** ``` USER: "Send a news card about the new feature release with an image" ASSISTANT: "I'll send a news notice card" [The assistant will use send_wecom_template_card_news_notice tool] ``` ### For Developers: Direct API Usage If you want to use this package directly in your Python code (not as an MCP server): ```python from wecom_bot_mcp_server import send_message, send_wecom_file, send_wecom_image, send_wecom_template_card # Send markdown message (uses default bot) await send_message( content="**Hello World!**", msg_type="markdown" ) # Send markdown_v2 message with tables and lists (default) await send_message( content="| Column1 | Column2 |\n|---------|---------|\\n| Value1 | Value2 |", msg_type="markdown_v2" ) # Send text message and mention users (use markdown for @mentions) await send_message( content="Hello <@user1> <@user2>", msg_type="markdown", mentioned_list=["user1", "user2"] ) # Send message to a specific bot await send_message( content="Build completed successfully!", msg_type="markdown_v2", bot_id="ci" # Send to CI bot ) # Send alert to alert bot await send_message( content="⚠️ High CPU usage detected!", msg_type="markdown_v2", bot_id="alert" ) # Send file to specific bot await send_wecom_file("/path/to/file.txt", bot_id="ci") # Send image to specific bot await send_wecom_image("/path/to/image.png", bot_id="alert") # Send template card (text_notice) await send_wecom_template_card( template_card_type="text_notice", template_card_source={"icon_url": "https://example.com/icon.png", "desc": "System"}, template_card_main_title={"title": "Deployment Success", "desc": "Production environment"}, template_card_card_action={"type": 1, "url": "https://example.com/dashboard"}, template_card_emphasis_content={"title": "100%", "desc": "Success Rate"}, bot_id="ci" ) ``` ### Multi-Bot Configuration in Code ```python from wecom_bot_mcp_server.bot_config import get_bot_registry, list_available_bots # List all available bots bots = list_available_bots() for bot in bots: print(f"Bot: {bot['id']} - {bot['name']}") # Check if a specific bot exists registry = get_bot_registry() if registry.has_bot("alert"): print("Alert bot is configured") # Get webhook URL for a specific bot url = registry.get_webhook_url("ci") ``` ## 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 # Run all tests with coverage uvx nox -s pytest # Run import tests only uvx nox -s test_imports # Run specific test file uvx nox -s pytest -- tests/test_message.py # Run tests with verbose output uvx nox -s pytest -- -v ``` ### 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 uvx nox -s build # Publish to PyPI (requires authentication) uvx nox -s publish ``` ### Continuous Integration The project uses GitHub Actions for CI/CD: - **MR Checks**: Runs on all pull requests, tests on Ubuntu, Windows, and macOS with Python 3.10, 3.11, and 3.12 - **Code Coverage**: Uploads coverage reports to Codecov - **Import Tests**: Ensures the package can be imported correctly after installation All dependencies are automatically tested during CI to catch issues early. ## Project Structure ``` wecom-bot-mcp-server/ ├── src/ │ └── wecom_bot_mcp_server/ │ ├── __init__.py │ ├── __main__.py │ ├── __version__.py │ ├── app.py # FastMCP application setup │ ├── server.py # Server entry point │ ├── message.py # Message and template card handling │ ├── file.py # File upload handling │ ├── image.py # Image upload handling │ ├── bot_config.py # Multi-bot configuration │ ├── utils.py # Utility functions │ ├── log_config.py # Logging configuration │ └── errors.py # Error definitions ├── tests/ │ ├── test_server.py │ ├── test_message.py │ ├── test_file.py │ ├── test_image.py │ └── test_bot_config.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