Tutorial: Build a WhatsApp Chatbot with n8n and Claude in 30 Minutes

WhatsApp has 2.7 billion active users. Here's how to build a functional WhatsApp chatbot with n8n 2.0 and Claude.

Architecture

WhatsApp Business API
      ↓ webhook
    n8n 2.0
      ├── Receive message
      ├── AI Agent (Claude)
      │   ├── Memory (Redis/Supabase)
      │   └── Tools (CRM, FAQ)
      └── Send response
      ↓
WhatsApp (user)

Prerequisites

• n8n v2.0+
• WhatsApp Business API account
• Anthropic API key
• (Optional) Supabase for memory

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Step 1: WhatsApp Webhook

1. Create an n8n workflow
2. Add a "Webhook" node (POST)
3. Configure the URL in Meta Business Platform
4. Events: messages, message_status

Step 2: Parse the Message

const body = $input.first().json.body;
const message = body.entry?.[0]?.changes?.[0]?.value?.messages?.[0];

return [{
  json: {
    from: message?.from,
    text: message?.text?.body,
    type: message?.type,
    messageId: message?.id
  }
}];

Step 3: AI Agent

1. Add an "AI Agent" node
2. Connect "Anthropic Chat Model" (Claude Sonnet or Opus)
3. System Prompt: friendly assistant, concise, able to escalate

Step 4: Memory

1. "Window Buffer Memory" node
2. Session ID: WhatsApp number ({{ $json.from }})
3. Window Size: 10 messages

Step 5: Send Response

{
  "method": "POST",
  "url": "https://graph.facebook.com/v18.0/PHONE_ID/messages",
  "headers": {
    "Authorization": "Bearer YOUR_TOKEN",
    "Content-Type": "application/json"
  },
  "body": {
    "messaging_product": "whatsapp",
    "to": "{{ $json.from }}",
    "type": "text",
    "text": { "body": "{{ $json.output }}" }
  }
}

Step 6: Human Escalation

• If response contains "transfer" → Slack notification to support
• If negative sentiment → Automatic escalation

Rate Limiting Anti-Ban

• Delay: min 1 second between messages
• Max: 30 messages/minute
• Window: 24h after last client message

Result

Webhook → Parser → AI Agent → Condition → Send WhatsApp

Your chatbot responds intelligently, remembers context, and escalates when needed.

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