{
  "workflow": {
    "id": 4591,
    "name": "Recipe recommendation engine with Bright Data MCP & OpenAI 4o mini",
    "views": 563,
    "recentViews": 0,
    "totalViews": 563,
    "createdAt": "2025-06-02T13:18:54.970Z",
    "description": "![Recipe Recommendation Engine with Bright Data MCP  OpenAI.png](fileId:1427)\n### Notice\nCommunity nodes can only be installed on self-hosted instances of n8n.\n\n### Who this is for\n\nRecipe Recommendation Engine with Bright Data MCP & OpenAI is a powerful automated workflow combines Bright Data's MCP for scraping trending or regional recipe data with OpenAI 4o mini to generate personalized recipe recommendations. \n\nThis automated workflow is designed for:\n\n**Food Bloggers & Culinary Creators** : Who want to automate the extraction and curation of recipes from across the web to generate content, compile cookbooks, or publish newsletters.\n\n**Nutritionists & Health Coaches** : Who need structured recipe data to analyze ingredients, calories, and nutrition for personalized meal planning or dietary tracking.\n\n**AI/ML Engineers & Data Scientists** : Building models that classify cuisines, predict recipes from ingredients, or generate dynamic meal suggestions using clean, structured datasets.\n\n**Grocery & Meal Kit Platforms** : Who aim to extract recipes to power recommendation engines, ingredient lists, or personalized meal plans.\n\n**Recipe Aggregator Startups** : Looking to scale recipe data collection, filtering, and standardization across diverse cooking websites with minimal human intervention.\n\n**Developers Integrating Cooking Features** : Into apps or digital assistants that offer recipe recommendations, step-by-step cooking instructions, or nutritional insights.\n\n### What problem is this workflow solving?\n\nThis workflow solves:\n\n- Automated recipe data extraction from any public URL\n\n- AI-driven structured data extraction\n\n- Scalable looped crawling and processing\n\n- Real-time notifications and data persistence\n\n### What this workflow does\n\n**1. Set Recipe Extract URL**\n- Configure the recipe website URL in the input node\n\n- Set your Bright Data zone name and authentication\n\n**2. Paginated Data Extract**\n- Triggers a paginated extraction across multiple pages (recipe listing, index, or search pages)\n\n- Returns a list of recipe links for processing\n\n**3. Loop Over Items**\n- Loops through the array of recipe links\n\n- Each link is passed individually to the scraping engine\n\n**4. Bright Data MCP Client (Per Recipe)**\n- Scrapes each individual recipe page using scrape_as_html\n\n- Smartly bypasses common anti-bot protections via Bright Data Web Unlocker\n\n**5. Structured Recipe Data Extract (via OpenAI GPT-4o mini)**\n- Converts raw HTML to clean text using an LLM preprocessing node\n\n- Uses OpenAI GPT-4o mini to extract structured data\n\n**6. Webhook Notification**\n- Pushes the structured recipe data to your configured webhook endpoint\n\n- Format: JSON payload, ideal for Slack, internal APIs, or dashboards\n\n**7. Save Response to Disk**\n- Saves the structured recipe JSON information to local file system\n\n### Pre-conditions\n\n1. You need to have a [Bright Data](https://brightdata.com/) account and do the necessary setup as mentioned in the \"Setup\" section below.\n2. You need to have an OpenAI Account.\n\n### Setup\n- Sign up at [Bright Data](https://brightdata.com/).\n- Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.\n- In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication).\n![MCPClientAccount.png](fileId:1426)\nThe Value field should be set with the\n**Bearer XXXXXXXXXXXXXX**. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token.\n- In n8n, configure the OpenAi account credentials.\n- Make sure to set the fields as part of **Set the Recipe Extract URL**. Remember to set the webhook_url to send a webhook notification of recipe response.\n- Set the desired local path in the **Write the structured content to disk** node to save the recipe response.\n\n### How to customize this workflow to your needs\n\nYou can tailor the Recipe Recommendation Engine workflow to better fit your specific use case by modifying the following key components:\n\n**1. Input Fields Node**\n- Update the Recipe URL to target specific cuisine sites or recipe types (e.g., vegan, keto, regional dishes).\n\n**2. LLM Configuration**\n- Swap out the OpenAI GPT-4o mini model with another provider (like Google Gemini) if you prefer.\n\n- Modify the structured data prompt to extract custom fields that you wish.\n\n**3. Webhook Notification**\n-  Configure the Webhook Notification node to point to your preferred integration (e.g., Slack, Discord, internal APIs).\n\n**4. Storage Destination**\n\nChange the **Save to Disk** node to store the structured recipe data in:\n\n- A cloud bucket (S3, GCS, Azure Blob etc.)\n\n- A database (MongoDB, PostgreSQL, Firestore)\n\n- Google Sheets or Airtable for spreadsheet-style access.\n\n",
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      },
      "name": "Recipe Recommendation Engine with Bright Data MCP & OpenAI",
      "tags": [],
      "nodes": [
        {
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          "name": "When clicking ‘Test workflow’",
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            "width": 440,
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            "content": "## Recipe Data Scraper"
          },
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        },
        {
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          "name": "List all tools for Bright Data",
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                  "name": "url",
                  "type": "string",
                  "value": "https://realfood.tesco.com/search.html?search=tomato%20pasta&sortby=Rating"
                },
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                  "name": "webhook_url",
                  "type": "string",
                  "value": "https://webhook.site/24878284-919d-4d39-bff0-5f36bfae17b6"
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                  "value": "https://realfood.tesco.com/search.html"
                }
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          "position": [
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          "parameters": {
            "text": "=Extract the paginated data from the provided content. \n\nHere's the content : {{ $json.result.content[0].text }}\n\nAppend the link with the Base URL as {{ $('Set the Recipe Extract URL').item.json.base_url }}",
            "messages": {
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                {
                  "message": "You are an expert data miner"
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            "hasOutputParser": true
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          "type": "n8n-nodes-base.code",
          "position": [
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          ],
          "parameters": {
            "jsCode": "return $input.first().json.output"
          },
          "typeVersion": 2
        },
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          "name": "Structured Output Parser for Paginated Data",
          "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
          "position": [
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          ],
          "parameters": {
            "jsonSchemaExample": "[{\n\t\"page_number\": \"page number in int\",\n\t\"link\": \"link to the web content\"\n}]"
          },
          "typeVersion": 1.2
        },
        {
          "id": "4e912c2c-12a1-45ee-a821-9e1fd873120c",
          "name": "Bright Data MCP Client For Recipe Extract",
          "type": "n8n-nodes-mcp.mcpClient",
          "notes": "Scrape a single webpage URL with advanced options for content extraction and get back the results in MarkDown language.",
          "position": [
            60,
            145
          ],
          "parameters": {
            "toolName": "scrape_as_html",
            "operation": "executeTool",
            "toolParameters": "={\n   \"url\": \"{{ $json.url }}\"\n} "
          },
          "credentials": {
            "mcpClientApi": {
              "id": "credential-id",
              "name": "mcpClientApi Credential"
            }
          },
          "notesInFlow": true,
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        },
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          "name": "Bright Data MCP Client For Recipe Extract Within The Loop",
          "type": "n8n-nodes-mcp.mcpClient",
          "notes": "Scrape a single webpage URL with advanced options for content extraction and get back the results in MarkDown language.",
          "position": [
            1480,
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          ],
          "parameters": {
            "toolName": "scrape_as_html",
            "operation": "executeTool",
            "toolParameters": "={\n   \"url\": \"{{ $json.link }}\"\n} "
          },
          "credentials": {
            "mcpClientApi": {
              "id": "credential-id",
              "name": "mcpClientApi Credential"
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          "name": "Structured Output Parser for Recipe Data Extract",
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          "position": [
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          "parameters": {
            "schemaType": "manual",
            "inputSchema": "{\n  \"$schema\": \"http://json-schema.org/schema#\",\n  \"title\": \"TescoRecipeSearchResults\",\n  \"type\": \"object\",\n  \"properties\": {\n    \"pageTitle\": { \"type\": \"string\" },\n    \"searchTerms\": { \"type\": \"string\" },\n    \"sortBy\": { \"type\": \"string\" },\n    \"numberOfResults\": { \"type\": \"integer\" },\n    \"numberOfPages\": { \"type\": \"integer\" },\n    \"numberOfFirstResult\": { \"type\": \"integer\" },\n    \"numberOfLastResult\": { \"type\": \"integer\" },\n    \"recipes\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"properties\": {\n          \"title\": { \"type\": \"string\" },\n          \"url\": { \"type\": \"string\" },\n          \"category\": { \"type\": \"string\" },\n          \"rating\": { \"type\": \"number\" },\n          \"serves\": { \"type\": \"integer\" },\n          \"dietaryOptions\": {\n            \"type\": \"array\",\n            \"items\": { \"type\": \"string\" }\n          },\n          \"isHealthy\": { \"type\": \"boolean\" }\n        },\n        \"required\": [\n          \"title\",\n          \"url\",\n          \"category\",\n          \"rating\",\n          \"serves\",\n          \"dietaryOptions\"\n        ],\n        \"additionalProperties\": false\n      }\n    }\n  },\n  \"required\": [\n    \"pageTitle\",\n    \"searchTerms\",\n    \"sortBy\",\n    \"numberOfResults\",\n    \"numberOfPages\",\n    \"numberOfFirstResult\",\n    \"numberOfLastResult\",\n    \"recipes\"\n  ],\n  \"additionalProperties\": false\n}\n"
          },
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        },
        {
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          "name": "Create a binary data",
          "type": "n8n-nodes-base.function",
          "position": [
            2200,
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          ],
          "parameters": {
            "functionCode": "items[0].binary = {\n  data: {\n    data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')\n  }\n};\nreturn items;"
          },
          "typeVersion": 1
        },
        {
          "id": "82630ed0-d321-42bd-ae68-e790228a61c7",
          "name": "Webhook Notification for Data Extract Within the Loop",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
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          "parameters": {
            "url": "={{ $('Set the Recipe Extract URL').item.json.webhook_url }}",
            "options": {},
            "sendBody": true,
            "contentType": "multipart-form-data",
            "bodyParameters": {
              "parameters": [
                {
                  "name": "recipe_content",
                  "value": "={{ $json.output.toJsonString() }}"
                }
              ]
            }
          },
          "typeVersion": 4.2
        },
        {
          "id": "c2b53242-8c0d-49a4-8cdb-27da64377d50",
          "name": "Write the structured content to disk",
          "type": "n8n-nodes-base.readWriteFile",
          "position": [
            2500,
            160
          ],
          "parameters": {
            "options": {},
            "fileName": "=d:\\Recipe-Structured-Data-{{ $('Loop Over Items').item.json.page_number }}.json",
            "operation": "write"
          },
          "typeVersion": 1
        },
        {
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          "name": "Structured Recipe Data Extract",
          "type": "@n8n/n8n-nodes-langchain.chainLlm",
          "position": [
            1740,
            160
          ],
          "parameters": {
            "text": "=Extract search data. Here's the content : \nOutput the data in JSON",
            "messages": {
              "messageValues": [
                {
                  "message": "You are an expert data miner"
                }
              ]
            },
            "promptType": "define",
            "hasOutputParser": true
          },
          "retryOnFail": true,
          "typeVersion": 1.6
        },
        {
          "id": "bd64603d-230b-4318-b365-b186826454f0",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            820,
            -160
          ],
          "parameters": {
            "width": 440,
            "height": 120,
            "content": "## Disclaimer\nThis template is only available on n8n self-hosted as it's making use of the community node for MCP Client."
          },
          "typeVersion": 1
        },
        {
          "id": "3715be91-c809-495c-8a4e-ca58cf9de999",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            820,
            0
          ],
          "parameters": {
            "color": 6,
            "width": 1860,
            "height": 540,
            "content": "## Structured Data Extract\n\nUsing MCP and LLMs for handling the Structured Data Extraction. Loop through the paginated dataset and handling the data extract.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "c5d846da-581a-4182-a52d-0e29b302150e",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
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          "parameters": {
            "width": 400,
            "height": 320,
            "content": "## Note\n\nDeals with the Recipe data extraction by utilizing the Bright Data MCP and OpenAI GPT 4o LLM.\n\n**Please make sure to set the input fields node with the Recipe URL\n\nPlease make sure to update the Webhook Notification URL of your interest**"
          },
          "typeVersion": 1
        },
        {
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          "name": "Sticky Note6",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
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          "parameters": {
            "color": 5,
            "width": 440,
            "height": 220,
            "content": "## LLM Usages\n\nOpenAI 4o mini LLM is being utilized for the structured data extraction handling."
          },
          "typeVersion": 1
        },
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          "position": [
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          "parameters": {
            "color": 7,
            "width": 400,
            "height": 400,
            "content": "## Logo\n\n\n![logo](https://images.seeklogo.com/logo-png/43/1/brightdata-logo-png_seeklogo-439974.png)\n"
          },
          "typeVersion": 1
        },
        {
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          "name": "OpenAI Chat Model for Paginated Data Extract",
          "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
          "position": [
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          "parameters": {
            "model": {
              "__rl": true,
              "mode": "list",
              "value": "gpt-4o-mini"
            },
            "options": {}
          },
          "credentials": {
            "openAiApi": {
              "id": "credential-id",
              "name": "openAiApi Credential"
            }
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          "typeVersion": 1.2
        },
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          "id": "566f7f77-8eed-4ea2-9402-ccb46a13bf52",
          "name": "OpenAI Chat Model for Structured Data Extract",
          "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
          "position": [
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          "parameters": {
            "model": {
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              "value": "gpt-4o-mini"
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              "id": "credential-id",
              "name": "openAiApi Credential"
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          },
          "typeVersion": 1.2
        },
        {
          "id": "fca8b6ce-a17c-416f-acc2-6a7a8bbf5b7b",
          "name": "Wait",
          "type": "n8n-nodes-base.wait",
          "position": [
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          "webhookId": "791cb0be-ba4a-417f-bcf2-ca8151bf16cd",
          "parameters": {
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      ],
      "active": false,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
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      "versionId": "79bcb4d2-0dd7-4759-a2f6-7636f054d543",
      "connections": {
        "Wait": {
          "main": [
            [
              {
                "node": "Bright Data MCP Client For Recipe Extract Within The Loop",
                "type": "main",
                "index": 0
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        "Loop Over Items": {
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                "type": "main",
                "index": 0
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                "node": "Code to output the array of paginated info",
                "type": "main",
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        },
        "Set the Recipe Extract URL": {
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        "List all tools for Bright Data": {
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                "node": "Set the Recipe Extract URL",
                "type": "main",
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              },
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                "type": "main",
                "index": 0
              }
            ]
          ]
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        "When clicking ‘Test workflow’": {
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                "node": "List all tools for Bright Data",
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        "Bright Data MCP Client For Recipe Extract": {
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                "type": "main",
                "index": 0
              }
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        "Structured Output Parser for Paginated Data": {
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                "node": "Paginated Data Extract",
                "type": "ai_outputParser",
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                "type": "ai_languageModel",
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                "index": 0
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                  "label": "How to set up a no-code CI/CD pipeline with GitHub and TravisCI"
                },
                {
                  "url": "https://n8n.io/blog/benefits-of-automation-and-n8n-an-interview-with-hubspots-hugh-durkin/",
                  "icon": "🎖",
                  "label": "Benefits of automation and n8n: An interview with HubSpot's Hugh Durkin"
                },
                {
                  "url": "https://n8n.io/blog/how-goomer-automated-their-operations-with-over-200-n8n-workflows/",
                  "icon": "🛵",
                  "label": "How Goomer automated their operations with over 200 n8n workflows"
                },
                {
                  "url": "https://n8n.io/blog/aws-workflow-automation/",
                  "label": "7 no-code workflow automations for Amazon Web Services"
                }
              ],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.set/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Edit Fields"
        },
        "iconData": {
          "icon": "pen",
          "type": "icon"
        },
        "displayName": "Edit Fields (Set)",
        "typeVersion": 3,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 39,
        "icon": "fa:sync",
        "name": "n8n-nodes-base.splitInBatches",
        "codex": {
          "data": {
            "alias": [
              "Loop",
              "Concatenate",
              "Batch",
              "Split",
              "Split In Batches"
            ],
            "resources": {
              "generic": [
                {
                  "url": "https://n8n.io/blog/how-uproc-scraped-a-multi-page-website-with-a-low-code-workflow/",
                  "icon": " 🕸️",
                  "label": "How uProc scraped a multi-page website with a low-code workflow"
                },
                {
                  "url": "https://n8n.io/blog/benefits-of-automation-and-n8n-an-interview-with-hubspots-hugh-durkin/",
                  "icon": "🎖",
                  "label": "Benefits of automation and n8n: An interview with HubSpot's Hugh Durkin"
                }
              ],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.splitinbatches/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Flow"
              ]
            }
          }
        },
        "group": "[\"organization\"]",
        "defaults": {
          "name": "Loop Over Items",
          "color": "#007755"
        },
        "iconData": {
          "icon": "sync",
          "type": "icon"
        },
        "displayName": "Loop Over Items (Split in Batches)",
        "typeVersion": 3,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 514,
        "icon": "fa:pause-circle",
        "name": "n8n-nodes-base.wait",
        "codex": {
          "data": {
            "alias": [
              "pause",
              "sleep",
              "delay",
              "timeout"
            ],
            "resources": {
              "generic": [
                {
                  "url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/",
                  "icon": "👥",
                  "label": "How to get started with CRM automation (with 3 no-code workflow ideas"
                },
                {
                  "url": "https://n8n.io/blog/aws-workflow-automation/",
                  "label": "7 no-code workflow automations for Amazon Web Services"
                }
              ],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.wait/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers",
                "Flow"
              ]
            }
          }
        },
        "group": "[\"organization\"]",
        "defaults": {
          "name": "Wait",
          "color": "#804050"
        },
        "iconData": {
          "icon": "pause-circle",
          "type": "icon"
        },
        "displayName": "Wait",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "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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"
        },
        "displayName": "Code",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 5,
            "name": "Development"
          },
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 838,
        "icon": "fa:mouse-pointer",
        "name": "n8n-nodes-base.manualTrigger",
        "codex": {
          "data": {
            "resources": {
              "generic": [],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.manualworkflowtrigger/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0"
          }
        },
        "group": "[\"trigger\"]",
        "defaults": {
          "name": "When clicking ‘Execute workflow’",
          "color": "#909298"
        },
        "iconData": {
          "icon": "mouse-pointer",
          "type": "icon"
        },
        "displayName": "Manual Trigger",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 1123,
        "icon": "fa:link",
        "name": "@n8n/n8n-nodes-langchain.chainLlm",
        "codex": {
          "data": {
            "alias": [
              "LangChain"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Chains",
                "Root Nodes"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Basic LLM Chain",
          "color": "#909298"
        },
        "iconData": {
          "icon": "link",
          "type": "icon"
        },
        "displayName": "Basic LLM Chain",
        "typeVersion": 2,
        "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",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "OpenAI Chat Model",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "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": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Output Parsers"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Structured Output Parser"
        },
        "iconData": {
          "icon": "code",
          "type": "icon"
        },
        "displayName": "Structured Output Parser",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1233,
        "icon": "file:readWriteFile.svg",
        "name": "n8n-nodes-base.readWriteFile",
        "codex": {
          "data": {
            "alias": [
              "Binary",
              "File",
              "Text",
              "Open",
              "Import",
              "Save",
              "Export",
              "Disk",
              "Transfer"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.readwritefile/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Files"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Read/Write Files from Disk"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Read/Write Files from Disk",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      }
    ],
    "categories": [
      {
        "id": 31,
        "name": "Content Creation"
      },
      {
        "id": 49,
        "name": "AI Summarization"
      }
    ],
    "image": [
      {
        "id": 1426,
        "url": "https://n8niostorageaccount.blob.core.windows.net/n8nio-strapi-blobs-prod/assets/MCP_Client_Account_ee010e7972.png"
      },
      {
        "id": 1427,
        "url": "https://n8niostorageaccount.blob.core.windows.net/n8nio-strapi-blobs-prod/assets/Recipe_Recommendation_Engine_with_Bright_Data_MCP_and_Open_AI_472f55b05a.png"
      }
    ]
  }
}