Mcp Wassenger is an MCP server that connects AI assistants to the Wassenger WhatsApp API, enabling automated messaging, chat management, and conversation analysis directly through Model Context Protocol clients. It links AI environments such as Claude Desktop, VS Code Copilot, Cursor, and Windsurf to WhatsApp accounts connected through Wassenger. Customer support teams, marketing specialists, and software developers use this server to automate customer communication workflows and inspect message histories using natural language prompts. The connector provides access to tools for sending text messages, sharing media files, replying to specific chat IDs, and scheduling outgoing messages for future delivery. Beyond basic chat interactions, the server allows AI models to summarize recent message threads, detect conversational tone, inspect contact details, and verify whether a phone number is registered on WhatsApp. Team operators can also create WhatsApp groups, manage participant permissions, trigger broadcast campaigns, and pull analytics on conversation volumes and agent response times. Supporting standard local transports and HTTP streaming, it streamlines WhatsApp business operations across supported AI tools.
Category: Communication & Messaging
Tags: automation, messaging, whatsapp
claude_desktop_config.json for Claude Desktop), register the server using the mcp-wassenger package: json { "mcpServers": { "wassenger": { "command": "npx", "args": ["-y", "mcp-wassenger"], "env": { "WASSENGER_API_KEY": "YOUR_API_KEY" } } } } 3. If your client supports remote HTTP streaming, configure the remote Wassenger MCP endpoint directly as described in the repository README. 4. Save your configuration and restart your AI client to expose the WhatsApp messaging tools.Send WhatsApp messages, images, and documents to individual contacts or phone numbers directly through AI chat interfaces using natural language commands. Summarize recent conversation threads, search message histories for specific keywords, and extract discussion topics across customer or internal WhatsApp chats. Schedule reminder notifications and automated announcements to be delivered to specific contacts or WhatsApp groups at specified dates and times. Create WhatsApp groups, update member participant lists, assign group administrator roles, and retrieve group invite links programmatically. Validate prospective phone numbers to confirm active WhatsApp accounts and inspect detailed profile data before launching marketing outreach campaigns.
Part of MCP Servers
Mcp Wassenger enables AI assistants to send messages, manage WhatsApp chats, inspect contact details, schedule future messages, and retrieve analytics. It exposes tools for sending multimedia messages, creating and moderating groups, verifying phone number validity, and generating conversation summaries and activity reports through natural language commands.
You can run Mcp Wassenger using npx by specifying mcp-wassenger in your MCP client configuration file, such as Claude Desktop or Cursor settings. Set the command to npx, pass -y and mcp-wassenger as arguments, and include your Wassenger API key in the environment variables before restarting the client.
Mcp Wassenger works with Model Context Protocol clients including Claude Desktop, VS Code Copilot, Cursor, Windsurf, Cline, Continue.dev, Zed Editor, Jan AI, and Open WebUI. It supports both local execution via standard I/O and remote HTTP streaming connections for clients compatible with streamable HTTP transports.
You need a registered Wassenger account with an active WhatsApp device connected, an API key generated from the Wassenger dashboard, and an MCP-compatible client environment. For local server execution, a modern Node.js runtime is required to execute the npm package.