{
  "workflow": {
    "id": 5969,
    "name": "Instant competitor product launch monitor with Bright Data & OpenAI to email/sheets",
    "views": 376,
    "recentViews": 0,
    "totalViews": 376,
    "createdAt": "2025-07-13T19:02:39.453Z",
    "description": "*This workflow contains community nodes that are only compatible with the self-hosted version of n8n.*\n\nThis workflow automatically monitors competitor product launches across news sites, press releases, and social channels. It saves you hours of manual tracking and ensures your team is instantly alerted when a rival announces something new.\n\n## Overview\n\nThe automation regularly scrapes predefined sources for mentions of your competitors combined with launch-related keywords. Bright Data provides reliable scraping, while OpenAI analyzes each article to extract key details (product name, features, launch date, pricing). Summaries are pushed to Slack and logged in Google Sheets so your marketing and product teams can react quickly.\n\n## Tools Used\n\n- **n8n** – Orchestrates the entire workflow\n- **Bright Data** – Scrapes news, blogs, and social posts without blocks\n- **OpenAI** – Extracts and summarizes launch information\n- **Slack** – Sends real-time alerts to a chosen channel\n- **Google Sheets** – Creates a searchable launch database\n\n## How to Install\n\n1. **Import the Workflow**: Upload the provided `.json` to your n8n instance.\n2. **Configure Bright Data**: Add your Bright Data credentials in the MCP Client node.\n3. **Set Up OpenAI**: Enter your OpenAI API key.\n4. **Connect Slack & Google Sheets**: Authorize both services and choose the target channel / spreadsheet.\n5. **Customize Sources**: Edit the list of competitor domains and launch keywords in the initial Set node.\n\n## Use Cases\n\n- **Product Marketing**: Track rival announcements to refine positioning.\n- **Sales Enablement**: Equip reps with up-to-date competitive intel.\n- **Competitive Intelligence**: Maintain a historical log of launches for trend analysis.\n- **Investor Relations**: Stay informed of market movements that affect valuation.\n\n## Connect with Me\n\n- **Website**: https://www.nofluff.online\n- **YouTube**: https://www.youtube.com/@YaronBeen/videos\n- **LinkedIn**: https://www.linkedin.com/in/yaronbeen/\n- **Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission)\n\n#n8n #automation #competitiveintelligence #productlaunch #brightdata #webscraping #openai #slackalerts #n8nworkflow #nocode #marketintel",
    "workflow": {
      "id": "uYgR0foKaUfC5jnc",
      "meta": {
        "instanceId": "60046904b104f0f72b2629a9d88fe9f676be4035769f1f08dad1dd38a76b9480",
        "templateCredsSetupCompleted": true
      },
      "name": "26 Monitor Competitor Product Launches",
      "tags": [],
      "nodes": [
        {
          "id": "4a5fffa9-521c-493a-83b1-0dce9f21ad07",
          "name": "OpenAI Chat Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
          "position": [
            400,
            260
          ],
          "parameters": {
            "model": {
              "__rl": true,
              "mode": "list",
              "value": "gpt-4o-mini"
            },
            "options": {}
          },
          "credentials": {
            "openAiApi": {
              "id": "credential-id",
              "name": "openAiApi Credential"
            }
          },
          "typeVersion": 1.2
        },
        {
          "id": "811e3e3e-27b0-4a2c-b1ee-423e4945b2a9",
          "name": "MCP Client",
          "type": "n8n-nodes-mcp.mcpClientTool",
          "position": [
            580,
            260
          ],
          "parameters": {
            "toolName": "scrape_as_markdown",
            "operation": "executeTool",
            "toolParameters": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Tool_Parameters', ``, 'json') }}"
          },
          "credentials": {
            "mcpClientApi": {
              "id": "credential-id",
              "name": "mcpClientApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "1caf6cda-6cdc-4a2a-88be-a19d4ee3db62",
          "name": "⏰ Daily Check (7AM)",
          "type": "n8n-nodes-base.scheduleTrigger",
          "position": [
            -40,
            0
          ],
          "parameters": {
            "rule": {
              "interval": [
                {
                  "triggerAtHour": 7
                }
              ]
            }
          },
          "typeVersion": 1.2
        },
        {
          "id": "8cca72fa-6a09-42b5-93a7-3a5cd166fd5c",
          "name": "🛠 Set Scrape Target (Verge Reviews)",
          "type": "n8n-nodes-base.set",
          "position": [
            160,
            0
          ],
          "parameters": {
            "options": {},
            "assignments": {
              "assignments": [
                {
                  "id": "1b2cc621-f0c5-43e1-bcd4-72850ac2bc57",
                  "name": "url",
                  "type": "string",
                  "value": "https://www.theverge.com/reviews"
                }
              ]
            }
          },
          "typeVersion": 3.4
        },
        {
          "id": "fa11746e-f206-4053-9709-863aa79f968c",
          "name": "🤖 Bright Data Scraper Agent",
          "type": "@n8n/n8n-nodes-langchain.agent",
          "position": [
            440,
            0
          ],
          "parameters": {
            "text": "=Use Bright Data Web Unlocker to scrape the latest product titles, release dates, and brief summaries from the following url.\n\nURL: {{ $json.url }}",
            "options": {},
            "promptType": "define",
            "hasOutputParser": true
          },
          "typeVersion": 2
        },
        {
          "id": "db8d08ef-9521-4fc1-a8c9-96a1f848e7db",
          "name": "🧾 Split & Format Each Review",
          "type": "n8n-nodes-base.code",
          "position": [
            900,
            0
          ],
          "parameters": {
            "jsCode": "// Sample input data from previous node\nconst items = $json[\"output\"];\n\n// Emit each review as a single item\nreturn items.map(review => {\n  return {\n    json: {\n      title: review.title,\n      url: \"https://www.theverge.com\" + review.url,\n      release_date: review.release_date,\n      summary: review.summary\n    }\n  };\n});\n"
          },
          "typeVersion": 2
        },
        {
          "id": "7d8d4349-8f85-42ce-9bf4-bf44da983838",
          "name": "📤 Email R&D: Product Alerts",
          "type": "n8n-nodes-base.gmail",
          "position": [
            1200,
            0
          ],
          "webhookId": "f47cb615-dd7d-47f1-900e-f069ef22e344",
          "parameters": {
            "sendTo": "user@example.com",
            "message": "=🚀 New Product Launch Spotted!\n\n📦 Product: {{ $json.title }}\n🗓 Release Date: {{ $json.release_date }}\n📝 Summary: {{ $json.summary }}\n🔗 Read Full Review → {{ $json.url }}",
            "options": {},
            "subject": "=🆕 New Product Review: {{ $json.title }}",
            "emailType": "text"
          },
          "credentials": {
            "gmailOAuth2": {
              "id": "credential-id",
              "name": "gmailOAuth2 Credential"
            }
          },
          "typeVersion": 2.1
        },
        {
          "id": "886e4fd7-d455-4ff8-a1d2-599b36b1de84",
          "name": "📊 Log to Google Sheet (Review History)",
          "type": "n8n-nodes-base.googleSheets",
          "position": [
            1400,
            0
          ],
          "parameters": {
            "columns": {
              "value": {
                "URL": "={{ $('🧾 Split & Format Each Review').item.json.url }}",
                "TItle": "={{ $('🧾 Split & Format Each Review').item.json.title }}",
                "Summary": "={{ $('🧾 Split & Format Each Review').item.json.summary }}",
                "Release date": "={{ $('🧾 Split & Format Each Review').item.json.release_date }}"
              },
              "schema": [
                {
                  "id": "TItle",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "TItle",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Release date",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Release date",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Summary",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Summary",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "URL",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "URL",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                }
              ],
              "mappingMode": "defineBelow",
              "matchingColumns": [],
              "attemptToConvertTypes": false,
              "convertFieldsToString": false
            },
            "options": {},
            "operation": "append",
            "sheetName": {
              "__rl": true,
              "mode": "list",
              "value": "gid=0",
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1Q6QXNKq7hFBQ18oiJwbhaOGxZqI22-rlL-Wahtxprf4/edit#gid=0",
              "cachedResultName": "Sheet1"
            },
            "documentId": {
              "__rl": true,
              "mode": "list",
              "value": "1Q6QXNKq7hFBQ18oiJwbhaOGxZqI22-rlL-Wahtxprf4",
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1Q6QXNKq7hFBQ18oiJwbhaOGxZqI22-rlL-Wahtxprf4/edit?usp=drivesdk",
              "cachedResultName": "Product Launches"
            }
          },
          "credentials": {
            "googleSheetsOAuth2Api": {
              "id": "credential-id",
              "name": "googleSheetsOAuth2Api Credential"
            }
          },
          "typeVersion": 4.6
        },
        {
          "id": "49d63a3e-ba19-4832-a3e0-804b0b7cda1f",
          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -80,
            -1020
          ],
          "parameters": {
            "color": 2,
            "width": 380,
            "height": 1200,
            "content": "## 🔶 **SECTION 1: Schedule & Scrape Target Configuration**\n\n🧩 **Nodes:**\n\n* ⏰ `Daily Check (7AM)`\n* 🛠 `Set Scrape Target (Verge Reviews)`\n\n---\n\n### 🧠 What’s Happening:\n\nThis section controls **when** and **what** to scrape.\n\n#### ⏰ `Schedule Trigger`\n\n* Automatically runs the workflow **every morning at 7AM**.\n* No manual checking needed!\n\n#### 🛠 `Edit Fields`\n\n* Sets the target scraping page:\n  `https://www.theverge.com/reviews`\n* You can easily switch this to other competitor sites (like TechCrunch or Wired) later.\n\n---\n\n### 💡 Why it matters:\n\nThis is where you **customize your intelligence source**. Just change the URL or keyword once — no coding needed.\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "538873a8-6b8c-4d4c-8f18-76f06608766f",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            400,
            -1260
          ],
          "parameters": {
            "color": 3,
            "width": 340,
            "height": 1440,
            "content": "## 🤖 **SECTION 2: Agent-Powered Scraping with Bright Data**\n\n🧩 **Node:**\n\n* 🤖 `Bright Data Scraper Agent`\n  🔗 Sub-nodes:\n* 🔮 OpenAI Chat Model\n* 🧩 MCP Client (Bright Data Tool)\n* 📦 Structured Output Parser\n\n---\n\n### 🧠 What’s Happening:\n\nThis is the **heart of the automation** — using a powerful AI agent connected to Bright Data’s scraping infrastructure.\n\n#### 🤖 `AI Agent`\n\n* Uses an **OpenAI agent** that understands your instructions.\n* Connects to **Bright Data MCP** to bypass anti-bot systems and extract clean product data.\n* Scrapes:\n\n  * 📦 Product Title\n  * 📅 Release Date\n  * 📝 Short Summary\n  * 🔗 URL (relative, so we'll fix that later)\n\n#### 📦 `Structured Output Parser`\n\n* Parses the AI agent’s response into structured JSON — ready for automation.\n\n---\n\n### 💡 Why it matters:\n\nEven a beginner can now use **AI + Bright Data** to scrape dynamic sites that normally block scrapers.\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "4d739fed-0ccb-4d24-ab57-a15a98cbfcdc",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            820,
            -1280
          ],
          "parameters": {
            "color": 6,
            "width": 260,
            "height": 1460,
            "content": "## 🧾 **SECTION 3: Split & Format Each Review**\n\n🧩 **Node:**\n\n* 🧾 `Split & Format Each Review`\n\n---\n\n### 🧠 What’s Happening:\n\nThis Code Node takes the array of product reviews and **splits them into one item each**.\n\n#### Code Features:\n\n* Converts relative URLs to full links (e.g., `/xyz` → `https://www.theverge.com/xyz`)\n* Outputs 10 clean JSON objects, one per review.\n\n```javascript\nreturn items.map(review => {\n  return {\n    json: {\n      title: review.title,\n      url: \"https://www.theverge.com\" + review.url,\n      release_date: review.release_date,\n      summary: review.summary\n    }\n  };\n});\n```\n\n---\n\n### 💡 Why it matters:\n\nThis lets you send **individual emails** and store **individual entries** — great for reporting, filtering, and team alerts.\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "1f97d84b-4459-4ad2-985f-41cf54736d88",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1160,
            -1260
          ],
          "parameters": {
            "color": 5,
            "width": 380,
            "height": 1440,
            "content": "## ✉️📊 **SECTION 4: Notify & Log the Insights**\n\n🧩 **Nodes:**\n\n* ✉️ `Email R&D: Product Alerts`\n* 📄 `Log to Google Sheet (Review History)`\n\n---\n\n### 🧠 What’s Happening:\n\nNow that the data is cleaned and structured, we act on it:\n\n#### ✉️ Gmail Node\n\n* Sends **one beautiful email per product** to the R\\&D team.\n* Contains:\n\n  * Product title\n  * Release date\n  * Summary\n  * Link to full article\n* Uses HTML formatting for clarity.\n\n#### 📄 Google Sheets Node\n\n* Appends each product to a sheet.\n* Serves as a **history log** to:\n\n  * Track past launches\n  * Prevent duplicate alerts\n  * Enable analysis later\n\n---\n\n### 💡 Why it matters:\n\nYour R\\&D team gets **instant alerts** about what competitors are launching — and you get a **central record** to refer to anytime.\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "63166a87-d9a0-48bf-8e93-e36530596a68",
          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1620,
            -1260
          ],
          "parameters": {
            "color": 7,
            "width": 380,
            "height": 240,
            "content": "## I’ll receive a tiny commission if you join Bright Data through this link—thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25"
          },
          "typeVersion": 1
        },
        {
          "id": "16610325-42f6-4838-83f0-82226303a119",
          "name": "Sticky Note9",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1780,
            -1020
          ],
          "parameters": {
            "color": 4,
            "width": 1300,
            "height": 320,
            "content": "=======================================\n            WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
          },
          "typeVersion": 1
        },
        {
          "id": "4dc735bf-5798-429b-904a-9819457ce281",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1780,
            -680
          ],
          "parameters": {
            "color": 4,
            "width": 1289,
            "height": 3978,
            "content": "# 🛠️ Monitor Competitor Product Launches (The Verge)\n\n> 🔄 Automated n8n workflow using Bright Data MCP to scrape reviews & notify R\\&D team\n\n---\n\n## 🔶 **SECTION 1: Schedule & Scrape Target Configuration**\n\n🧩 **Nodes:**\n\n* ⏰ `Daily Check (7AM)`\n* 🛠 `Set Scrape Target (Verge Reviews)`\n\n---\n\n### 🧠 What’s Happening:\n\nThis section controls **when** and **what** to scrape.\n\n#### ⏰ `Schedule Trigger`\n\n* Automatically runs the workflow **every morning at 7AM**.\n* No manual checking needed!\n\n#### 🛠 `Edit Fields`\n\n* Sets the target scraping page:\n  `https://www.theverge.com/reviews`\n* You can easily switch this to other competitor sites (like TechCrunch or Wired) later.\n\n---\n\n### 💡 Why it matters:\n\nThis is where you **customize your intelligence source**. Just change the URL or keyword once — no coding needed.\n\n---\n\n## 🤖 **SECTION 2: Agent-Powered Scraping with Bright Data**\n\n🧩 **Node:**\n\n* 🤖 `Bright Data Scraper Agent`\n  🔗 Sub-nodes:\n* 🔮 OpenAI Chat Model\n* 🧩 MCP Client (Bright Data Tool)\n* 📦 Structured Output Parser\n\n---\n\n### 🧠 What’s Happening:\n\nThis is the **heart of the automation** — using a powerful AI agent connected to Bright Data’s scraping infrastructure.\n\n#### 🤖 `AI Agent`\n\n* Uses an **OpenAI agent** that understands your instructions.\n* Connects to **Bright Data MCP** to bypass anti-bot systems and extract clean product data.\n* Scrapes:\n\n  * 📦 Product Title\n  * 📅 Release Date\n  * 📝 Short Summary\n  * 🔗 URL (relative, so we'll fix that later)\n\n#### 📦 `Structured Output Parser`\n\n* Parses the AI agent’s response into structured JSON — ready for automation.\n\n---\n\n### 💡 Why it matters:\n\nEven a beginner can now use **AI + Bright Data** to scrape dynamic sites that normally block scrapers.\n\n---\n\n## 🧾 **SECTION 3: Split & Format Each Review**\n\n🧩 **Node:**\n\n* 🧾 `Split & Format Each Review`\n\n---\n\n### 🧠 What’s Happening:\n\nThis Code Node takes the array of product reviews and **splits them into one item each**.\n\n#### Code Features:\n\n* Converts relative URLs to full links (e.g., `/xyz` → `https://www.theverge.com/xyz`)\n* Outputs 10 clean JSON objects, one per review.\n\n```javascript\nreturn items.map(review => {\n  return {\n    json: {\n      title: review.title,\n      url: \"https://www.theverge.com\" + review.url,\n      release_date: review.release_date,\n      summary: review.summary\n    }\n  };\n});\n```\n\n---\n\n### 💡 Why it matters:\n\nThis lets you send **individual emails** and store **individual entries** — great for reporting, filtering, and team alerts.\n\n---\n\n## ✉️📊 **SECTION 4: Notify & Log the Insights**\n\n🧩 **Nodes:**\n\n* ✉️ `Email R&D: Product Alerts`\n* 📄 `Log to Google Sheet (Review History)`\n\n---\n\n### 🧠 What’s Happening:\n\nNow that the data is cleaned and structured, we act on it:\n\n#### ✉️ Gmail Node\n\n* Sends **one beautiful email per product** to the R\\&D team.\n* Contains:\n\n  * Product title\n  * Release date\n  * Summary\n  * Link to full article\n* Uses HTML formatting for clarity.\n\n#### 📄 Google Sheets Node\n\n* Appends each product to a sheet.\n* Serves as a **history log** to:\n\n  * Track past launches\n  * Prevent duplicate alerts\n  * Enable analysis later\n\n---\n\n### 💡 Why it matters:\n\nYour R\\&D team gets **instant alerts** about what competitors are launching — and you get a **central record** to refer to anytime.\n\n---\n\n## 🎯 Final Thoughts\n\nEven if you’re a complete beginner:\n\n* You don’t need to write code (just paste small pieces).\n* You’re scraping dynamic sites legally & cleanly via Bright Data.\n* You’re using AI + n8n to automate competitive intelligence.\n\n---\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "b734d682-96ea-4a55-8bfd-1ee0a54fee25",
          "name": "Auto-fixing Output Parser",
          "type": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
          "position": [
            720,
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          ],
          "parameters": {
            "options": {}
          },
          "typeVersion": 1
        },
        {
          "id": "12810685-db1c-41b4-a45b-75eb17e62837",
          "name": "OpenAI Chat Model1",
          "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
          "position": [
            700,
            480
          ],
          "parameters": {
            "model": {
              "__rl": true,
              "mode": "list",
              "value": "gpt-4o-mini"
            },
            "options": {}
          },
          "credentials": {
            "openAiApi": {
              "id": "credential-id",
              "name": "openAiApi Credential"
            }
          },
          "typeVersion": 1.2
        },
        {
          "id": "76e60d57-1853-45ab-809c-457d8f425765",
          "name": "Structured Output Parser1",
          "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
          "position": [
            860,
            480
          ],
          "parameters": {
            "jsonSchemaExample": "[\n  {\n    \"title\": \"The best earbuds we’ve tested for 2025\",\n    \"url\": \"https://www.theverge.com/21309820/best-wireless-earbuds\",\n    \"release_date\": \"2025-07-04\",\n    \"summary\": \"This review highlights the best earbuds from brands like Apple, Bose, Samsung, and Sony, suited for various preferences.\"\n  },\n  {\n    \"title\": \"The Loop Micro is my new favorite bicycle phone mount\",\n    \"url\": \"https://www.theverge.com/reviews/697356/loop-micro-best-bike-mount-review\",\n    \"release_date\": \"2025-07-04\",\n    \"summary\": \"The Loop Micro is praised for its design and functionality, ideally suited for cyclists wanting to mount their phones securely.\"\n  },\n  {\n    \"title\": \"The best robot vacuum and mop to buy right now\",\n    \"url\": \"https://www.theverge.com/tech/625409/best-robot-vacuum-mops\",\n    \"release_date\": \"2025-07-03\",\n    \"summary\": \"A comparison of the top robot vacuum and mop combos available, offering insights on their cleaning capabilities.\"\n  },\n  {\n    \"title\": \"Whoop MG review: a big whoop for a small crowd\",\n    \"url\": \"https://www.theverge.com/fitness-tracker-review/696156/whoop-mg-review-wearables-fitness-tracker-health\",\n    \"release_date\": \"2025-07-03\",\n    \"summary\": \"The Whoop MG wearable is evaluated, targeting athletes specifically, and the review discusses its features and effectiveness.\"\n  },\n  {\n    \"title\": \"Nothing Headphone 1 review: head-turning\",\n    \"url\": \"https://www.theverge.com/headphone-review/695609/nothing-headphone-1-review\",\n    \"release_date\": \"2025-07-01\",\n    \"summary\": \"This review assesses the Nothing Headphone 1, exploring its design and tech, and notes its distinctive style among Bluetooth headphones.\"\n  }\n]\n"
          },
          "typeVersion": 1.2
        }
      ],
      "active": false,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
      },
      "versionId": "2c5d01ae-eba8-436c-9982-8c1af7540427",
      "connections": {
        "MCP Client": {
          "ai_tool": [
            [
              {
                "node": "🤖 Bright Data Scraper Agent",
                "type": "ai_tool",
                "index": 0
              }
            ]
          ]
        },
        "OpenAI Chat Model": {
          "ai_languageModel": [
            [
              {
                "node": "🤖 Bright Data Scraper Agent",
                "type": "ai_languageModel",
                "index": 0
              }
            ]
          ]
        },
        "OpenAI Chat Model1": {
          "ai_languageModel": [
            [
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        "displayName": "Gmail",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 6,
            "name": "Communication"
          },
          {
            "id": 28,
            "name": "HITL"
          }
        ]
      },
      {
        "id": 565,
        "icon": "fa:sticky-note",
        "name": "n8n-nodes-base.stickyNote",
        "codex": {
          "data": {
            "alias": [
              "Comments",
              "Notes",
              "Sticky"
            ],
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Sticky Note",
          "color": "#FFD233"
        },
        "iconData": {
          "icon": "sticky-note",
          "type": "icon"
        },
        "displayName": "Sticky Note",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 834,
        "icon": "file:code.svg",
        "name": "n8n-nodes-base.code",
        "codex": {
          "data": {
            "alias": [
              "cpde",
              "Javascript",
              "JS",
              "Python",
              "Script",
              "Custom Code",
              "Function"
            ],
            "details": "The Code node allows you to execute JavaScript in your workflow.",
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.code/"
                }
              ]
            },
            "categories": [
              "Development",
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers",
                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Code"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
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        "displayName": "Code",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 5,
            "name": "Development"
          },
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 839,
        "icon": "fa:clock",
        "name": "n8n-nodes-base.scheduleTrigger",
        "codex": {
          "data": {
            "alias": [
              "Time",
              "Scheduler",
              "Polling",
              "Cron",
              "Interval"
            ],
            "resources": {
              "generic": [],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.scheduletrigger/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0"
          }
        },
        "group": "[\"trigger\",\"schedule\"]",
        "defaults": {
          "name": "Schedule Trigger",
          "color": "#31C49F"
        },
        "iconData": {
          "icon": "clock",
          "type": "icon"
        },
        "displayName": "Schedule Trigger",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 1119,
        "icon": "fa:robot",
        "name": "@n8n/n8n-nodes-langchain.agent",
        "codex": {
          "data": {
            "alias": [
              "LangChain",
              "Chat",
              "Conversational",
              "Plan and Execute",
              "ReAct",
              "Tools"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Agents",
                "Root Nodes"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "AI Agent",
          "color": "#404040"
        },
        "iconData": {
          "icon": "robot",
          "type": "icon"
        },
        "displayName": "AI Agent",
        "typeVersion": 3,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1153,
        "icon": "file:openAiLight.svg",
        "name": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Language Models",
                "Root Nodes"
              ],
              "Language Models": [
                "Chat Models (Recommended)"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "OpenAI Chat Model"
        },
        "iconData": {
          "type": "file",
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        "displayName": "OpenAI Chat Model",
        "typeVersion": 1,
        "nodeCategories": [
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            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1175,
        "icon": "fa:tools",
        "name": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.outputparserautofixing/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Output Parsers"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Auto-fixing Output Parser"
        },
        "iconData": {
          "icon": "tools",
          "type": "icon"
        },
        "displayName": "Auto-fixing Output Parser",
        "typeVersion": 1,
        "nodeCategories": [
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            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1179,
        "icon": "fa:code",
        "name": "@n8n/n8n-nodes-langchain.outputParserStructured",
        "codex": {
          "data": {
            "alias": [
              "json",
              "zod"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.outputparserstructured/"
                }
              ]
            },
            "categories": [
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              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Output Parsers"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Structured Output Parser"
        },
        "iconData": {
          "icon": "code",
          "type": "icon"
        },
        "displayName": "Structured Output Parser",
        "typeVersion": 1,
        "nodeCategories": [
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            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      }
    ],
    "categories": [
      {
        "id": 32,
        "name": "Market Research"
      },
      {
        "id": 49,
        "name": "AI Summarization"
      }
    ],
    "image": []
  }
}