mcp-wassenger

This MCP server integrates Wassenger's WhatsApp API with any MCP-compatible AI client. It enables you to send messages, analyze conversations, manage chats and groups, schedule messages, and perform bulk operations through natural language prompts and AI tooling. The server exposes a set of MCP tools geared toward core messaging, conversation management, group administration, analytics, and automation, so you can orchestrate WhatsApp workflows directly from your AI assistant (such as ChatGPT, Claude, or other MCP clients) without needing handwritten API calls. If your MCP client supports HTTP streaming, you can leverage streaming responses for real-time updates; otherwise, the server will present standard request/response interactions for the Wassenger endpoints. Typical usage involves authenticating with Wassenger (via an API key or configured credentials), then issuing MCP tool prompts like sending a message, summarizing a conversation, or scheduling a message to a contact or group through natural language commands.

Prerequisites:

• Node.js (version 14 or newer) and npm installed on your system
• Access rights to install npm packages or run local server

Installation steps:

1. Install the MCP Wassenger package locally (or globally if you prefer): npm install mcp-wassenger

2. Set up your environment variables (adjust as needed):

   • Create a .env file or export variables in your shell
   • Example: WASSENGER_API_KEY=your_wassenger_api_key

3. Start the MCP Wassenger server: node server.js

4. Verify the server is running by hitting the configured MCP port (default /check or /health endpoints) or by running a basic MCP test request from your MCP client.

If you are using a containerized setup, you can adapt these steps to a Docker workflow by mounting your env and running the container with the appropriate port mappings.

Tips and common considerations:

• Ensure your Wassenger API credentials are valid and have the required permissions for the actions you intend to perform (sending messages, reading chats, etc.).
• If your MCP client expects HTTP streaming, enable or configure streaming support as described in your client docs and in the Wassenger MCP integration notes.
• Check logs if you encounter authentication or connection errors; verify network access to Wassenger endpoints and that API keys are correctly loaded.
• You can customize environment variables or add more config options as needed for your deployment (e.g., port, log level, timeouts).
• The server name in MCP config is 'wassenger', but you can rename it in your MCP client configuration if desired to reflect your environment.