AutomationFlowsAI & RAG › AI Chat Agent for Twitter Automation

AI Chat Agent for Twitter Automation

Original n8n title: Automatizacion X

Automatizacion X. Uses chatTrigger, lmChatOpenAi, memoryBufferWindow, twitterTool. Chat trigger; 6 nodes.

Chat trigger trigger★★☆☆☆ complexityAI-powered6 nodesChat TriggerOpenAI ChatMemory Buffer WindowTwitter ToolAgent
AI & RAG Trigger: Chat trigger Nodes: 6 Complexity: ★★☆☆☆ AI nodes: yes Added:

This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.

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
{
  "id": "WCh8N9PrO0UIwrqW",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "name": "Automatizacion X",
  "tags": [],
  "nodes": [
    {
      "id": "a51d67d2-ef4a-47c3-8206-51f2c1067128",
      "name": "When chat message received",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        0,
        0
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "702d2f29-c9cb-46aa-bdc2-ccd68ab24a1c",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        200,
        240
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o",
          "cachedResultName": "gpt-4o"
        },
        "options": {}
      },
      "typeVersion": 1.2
    },
    {
      "id": "6d65d809-e2b3-4884-ad1a-7738ac9ebbb7",
      "name": "Simple Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        400,
        240
      ],
      "parameters": {},
      "typeVersion": 1.3
    },
    {
      "id": "2f247c72-8f90-49f9-9982-bf94c044b8bb",
      "name": "first tweet",
      "type": "n8n-nodes-base.twitterTool",
      "position": [
        560,
        240
      ],
      "parameters": {
        "text": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Text', ``, 'string') }}",
        "additionalFields": {}
      },
      "typeVersion": 2
    },
    {
      "id": "0c298eab-4a0c-4835-ab93-6ba44d81fb5c",
      "name": "hilo",
      "type": "n8n-nodes-base.twitterTool",
      "position": [
        740,
        240
      ],
      "parameters": {
        "text": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Text', ``, 'string') }}",
        "additionalFields": {
          "inReplyToStatusId": {
            "__rl": true,
            "mode": "id",
            "value": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Reply_to_Tweet', `Debes hacer reply justo al tweet anterior`, 'string') }}"
          }
        }
      },
      "typeVersion": 2
    },
    {
      "id": "26971067-45ac-43c4-aa8c-15976de81d31",
      "name": "Agente X",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        320,
        0
      ],
      "parameters": {
        "options": {
          "systemMessage": "=# Rol\nEres un redactor de tweets informtivos, redactados de manera amigable y entendible.\n\n# Herramientas\n- Utiliza la herramienta *first tweet* para crear el primer tuit.\n- Utiliza la herramienta *hilo* para crear las respuestas a cada tuit anterior, formando un hilo coherente y continuo.\n- Cada tuit (tanto el primero como las respuestas) debe tener un m\u00e1ximo de 270 caracteres.\n- El estilo debe ser en primera persona, cercano y conversacional, como si fuera escrito por m\u00ed.\n- Mant\u00e9n un tono natural y \u00fanico, con posibles expresiones personales y un enfoque narrativo.\n- El contenido de cada tuit debe conectar de forma fluida con el anterior, para que se perciba como un hilo narrativo.\n\n#Objetivo:\nGenerar un hilo atractivo y coherente, que invite a la interacci\u00f3n.\n\n# Ejemplo de estructura:\nPrimer tuit (con first tweet): \nSegundo tuit (con hilo): Responde al primer tweet\nTercer tuit (con hilo): Responde al segundo tweet\n"
        }
      },
      "typeVersion": 1.8
    }
  ],
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "956762aa-46a5-42eb-bfcd-bf61548456ae",
  "connections": {
    "hilo": {
      "ai_tool": [
        [
          {
            "node": "Agente X",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "first tweet": {
      "ai_tool": [
        [
          {
            "node": "Agente X",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Simple Memory": {
      "ai_memory": [
        [
          {
            "node": "Agente X",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Agente X",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "When chat message received": {
      "main": [
        [
          {
            "node": "Agente X",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
Pro

For the full experience including quality scoring and batch install features for each workflow upgrade to Pro

About this workflow

Automatizacion X. Uses chatTrigger, lmChatOpenAi, memoryBufferWindow, twitterTool. Chat trigger; 6 nodes.

Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →

More AI & RAG workflows → · Browse all categories →

Related workflows

Workflows that share integrations, category, or trigger type with this one. All free to copy and import.

AI & RAG

AI Agent : Google calendar assistant using OpenAI. Uses chatTrigger, lmChatOpenAi, memoryBufferWindow, googleCalendarTool. Chat trigger; 13 nodes.

Chat Trigger, OpenAI Chat, Memory Buffer Window +2
AI & RAG

OpenSea AI-Powered Insights via Telegram. Uses chatTrigger, telegramTrigger, lmChatOpenAi, memoryBufferWindow. Chat trigger; 13 nodes.

Chat Trigger, Telegram Trigger, OpenAI Chat +4
AI & RAG

Build an MCP server with Airtable. Uses chatTrigger, agent, memoryBufferWindow, mcpClientTool. Chat trigger; 13 nodes.

Chat Trigger, Agent, Memory Buffer Window +4
AI & RAG

Build an MCP server with Airtable. Uses chatTrigger, agent, memoryBufferWindow, mcpClientTool. Chat trigger; 13 nodes.

Chat Trigger, Agent, Memory Buffer Window +4
AI & RAG

This template is a simple AI Agent that acts as a Google Calendar Assistant. It is designed for beginners to have their "first AI Agent" performing common tasks and to help them understand how it work

Chat Trigger, OpenAI Chat, Memory Buffer Window +2