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Customer Support AI Agent

Customer Support AI Agent. Uses agent, lmChatOpenAi, mcpClientTool, memoryBufferWindow. Webhook trigger; 5 nodes.

Webhook trigger★★☆☆☆ complexityAI-powered5 nodesAgentLm Chat Open AiMcp Client ToolMemory Buffer Window
AI & RAG Trigger: Webhook Nodes: 5 Complexity: ★★☆☆☆ AI nodes: yes

The workflow JSON

Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →

Download .json
{
  "name": "Customer Support AI Agent",
  "id": "wf-001",
  "nodes": [
    {
      "name": "Webhook Trigger",
      "type": "n8n-nodes-base.webhook",
      "parameters": {
        "path": "support",
        "httpMethod": "POST",
        "authentication": "none"
      },
      "position": [
        200,
        300
      ]
    },
    {
      "name": "AI Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "parameters": {
        "agentType": "conversationalAgent"
      },
      "position": [
        400,
        300
      ]
    },
    {
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "parameters": {
        "model": "gpt-4o",
        "temperature": 0.7
      },
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      },
      "position": [
        400,
        500
      ]
    },
    {
      "name": "MCP Client",
      "type": "@n8n/n8n-nodes-langchain.mcpClientTool",
      "parameters": {
        "sseEndpoint": "https://external-mcp-server.example.com/sse"
      },
      "position": [
        600,
        500
      ]
    },
    {
      "name": "Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "parameters": {
        "contextWindowLength": 10
      },
      "position": [
        400,
        700
      ]
    }
  ],
  "connections": {
    "Webhook Trigger": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "MCP Client": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    }
  }
}

Credentials you'll need

Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.

About this workflow

Customer Support AI Agent. Uses agent, lmChatOpenAi, mcpClientTool, memoryBufferWindow. Webhook trigger; 5 nodes.

Source: https://github.com/Trusera/ai-bom/blob/main/examples/demo-project/workflows/customer-support-agent.json — original creator credit. Request a take-down →

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