WhatsApp MCP

Human-in-the-Loop for AI Agents via WhatsApp

This is an MCP (Model Context Protocol) server that enables AI agents (like Claude or Cursor) to interact directly with you via WhatsApp. It bridges the gap between your autonomous AI and your phone, allowing for runtime confirmations, permission requests, or simple status updates while you are away from your computer.

• AI agent messaging
• AI agent confirmations
• Agent interrupt system
• AI alerts
• MCP server
• Cursor MCP
• Claude Desktop MCP
• AI notifications

Perfect for

• Cursor
• Claude Desktop
• Claude Code
• OpenCode
• Codex
• Autonomous AI workflows

Example

AI: Deploy to production?

WhatsApp: [YES] [NO]

You: YES

Agent continues.

🚀 Quick Start (NPX)

Since this package is published to NPM, you can run it directly via npx in your MCP configuration.

Cursor / Claude Configuration

Add this to your MCP configuration file:

{
  "mcpServers": {
    "whatsapp-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@mhrj/whatsapp-mcp"
      ],
      "env": {
        "WHATSAPP_TARGET_NUMBER": "1234567890@s.whatsapp.net"
      }
    }
  }
}

Note about Allowed Numbers: WHATSAPP_TARGET_NUMBER is the default recipient for all messages. However, if your target is a Whatsapp Group, any member of the group would be able to answer the AI by default. To restrict replies only to specific numbers (to prevent unauthorized people from answering), you can optionally add a comma-separated list of numbers as an environment variable: "WHATSAPP_ALLOWED_NUMBERS": "123@s.whatsapp.net,456@s.whatsapp.net". If set, the AI will ONLY honor responses from these specific matching users.

Troubleshooting npx: executable file not found in $PATH or env: node: No such file or directory: If your IDE/Agent complains it cannot find npx or node, it's because GUI apps (like Cursor) don't inherit your terminal's $PATH. To fix this, explicitly pass your PATH in the MCP env config.

json

Copy

      "env": {
        "PATH": "/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin",
        "WHATSAPP_TARGET_NUMBER": "1234567890@s.whatsapp.net"
      }

Authentication (First time only)

The very first time you use the MCP server, it needs to authenticate with WhatsApp Web:

1. Call the connect tool via your Agent, or just use any WhatsApp tool normally. If the session is not authenticated yet, the server will trigger authentication automatically.
2. The tool result will return the QR code image directly in MCP content so modern clients can render it inline.
3. If your client does not render inline images, the server also tries to write a local fallback HTML page under ~/.whatsapp-mcp/qr.html.
4. Open WhatsApp on your phone -> Linked Devices -> Link a Device, and scan the QR.
5. The authentication session is saved to your home directory (~/.whatsapp-mcp/baileys_auth_info), so you don't need to scan it again across restarts.

Remote "Auto-Pilot" Workflow (Skip IDE Prompts)

To make your AI agent run fully autonomously and only ask for permissions/guidance via WhatsApp (allowing you to step away from your computer):

1. Remove IDE Security Blockers: When your agent (like Cursor or Claude) asks for permission to run a command or read a file, select Always Allow (or enable "yolo" mode in settings). This gives the agent the mechanical freedom to operate without pausing indefinitely for a UI click.
2. Add a .cursorrules (or system prompt) file: You must explicitly instruct the AI to use WhatsApp whenever it reaches a logical decision point. Create a .cursorrules file in your project root with this exact prompt:

# Human-in-the-Loop via WhatsApp
You are connected to the user via the `whatsapp-mcp` server. 
Whenever you are about to make significant/destructive changes, run a deployment, or whenever you need the user's permission/opinion to proceed with a plan, you MUST use the `ask_question` tool to ask the user on WhatsApp. 
DO NOT simply ask for confirmation in the IDE chat interface. You must wait for the `ask_question` tool to return the user's WhatsApp reply before proceeding with your task.

With these two steps, the AI will proactively proactively use the ask_question tool to beam its logical permission requests directly to your phone instead of freezing in the IDE.

Features & Tools

• connect: Connects to the WhatsApp network. If not logged in, returns a native QR image in the tool result and may also provide a local HTML fallback.
• disconnect: Completely logs out of WhatsApp and invalidates the session credentials.
• send_message: Sends a one-way notification. Supports optional WhatsApp markdown mapping (*bold*). If the server is not connected yet, it auto-triggers authentication first.
• ask_question: Sends a prompt and blocks execution until a reply is received (with a timeout). Concurrent questions are smartly queued and tagged with references. If the server is not connected yet, it auto-triggers authentication first.
• get_incoming_messages: Polls unsolicited inbound WhatsApp messages so agents that do not support server-side sampling can still retrieve them.
• get_status: Provides agent connection state monitoring, including auth state such as connected, connecting, or qr_pending.
• Server instructions + prompt: The server exports built-in workflow instructions and a whatsapp-autopilot prompt so clients can guide agents toward connect-first and WhatsApp-first behavior.

Local Development

If you'd like to run it locally from source:

1. Clone the repository and npm install
2. npm run build
3. Link via absolute path instead of npx.

License

This project is licensed under the ISC License.

Third-Party Licenses

This project utilizes the following open-source libraries:

• @modelcontextprotocol/sdk - MIT License
• @whiskeysockets/baileys - MIT License
• Other dependencies (express, pino, qrcode, etc.) are licensed under permissive licenses (MIT/BSD).

Discoverability keywords

• Human in the loop AI
• AI approvals
• Runtime approvals
• Agent notifications
• Agent approval workflow
• Cursor WhatsApp integration
• Claude WhatsApp integration
• Autonomous agents
• Cursor power users
• Remote workers

What problem does this solve?

• AI agents often get blocked waiting for approvals/questions when you step away from the IDE.
• WhatsApp MCP notifies you and collects confirmations from your phone so agents can continue safely.

Who it's for

• Cursor agent / Claude Desktop users
• Solo builders shipping agentic workflows
• DevOps & automation teams needing runtime approvals