{
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    "name": "Search Google, Bing, Yandex & extract structured results with Bright Data MCP & Google Gemini",
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    "createdAt": "2025-06-09T14:16:39.530Z",
    "description": "![Perform Google, Bing, Yandex Search with Bright Data MCP Agent  Google Gemini.png](fileId:1466)\n### Notice\nCommunity nodes can only be installed on self-hosted instances of n8n.\n\n### Who this is for?\n\nThe Search Engine Intelligence Extractor is a powerful n8n automation that leverages Bright Data’s MCP based AI Agents to simulate human-like searches across Google, Bing, and Yandex, and then distills clean, structured insights using Google Gemini.\n\nThis workflow is tailored for:\n\n- SEO analysts researching competitors or market trends\n\n- Market researchers needing real-time search visibility\n\n- Journalists & content writers gathering contextual insights\n\n- AI developers creating intelligent assistants\n\n- Digital marketers tracking brand mentions or news\n\n### What problem is this workflow solving?\n\nTraditional scraping of search engines is often blocked, cluttered, or filled with irrelevant information. Manually analyzing and cleaning this data for insight is time-consuming.\n\nThis workflow solves the problem by:\n\n- Simulating real user search behavior via Bright Data MCP based AI Agent\n\n- Performing multi-platform search (Google, Bing, Yandex) in one unified flow\n\n- Extracting clean, human-readable results (stripping ads, navigation, etc.)\n\n- Structuring the content using Google Gemini LLM\n\n- Automating delivery via Webhook or saving to disk\n\n### What this workflow does\n\n**Input Fields Node:**\n\n- Accepts the search query\n\n- Accepts action for example - Perform a google search. Replace the action with bing, yandex etc. for other search providers\n\n- Accepts Webhook notification URL\n\n**Bright Data MCP Agent Execution:**\n\n- Triggers Bright Data’s intelligent search agent\n\n- Handles search navigation, result loading, pagination\n\n**Human Readable Data Extractor:**\n\n- Cleanses HTML, removes ads, footers, irrelevant links\n\n- Produces a readable narrative of results\n\n**Final Output Handling:**\n\n- Saves the processed response to disk\n\n- Sends the structured data to a Webhook for real-time use\n\n### Pre-conditions\n\n1. Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - [model-context-protocol](https://www.anthropic.com/news/model-context-protocol)\n2. You need to have the [Bright Data](https://brightdata.com/) account and do the necessary setup as mentioned in the **Setup** section below.\n3. You need to have the Google Gemini API Key. Visit [Google AI Studio](https://aistudio.google.com/)\n3. You need to install the Bright Data MCP Server [@brightdata/mcp](https://www.npmjs.com/package/@brightdata/mcp)\n4. You need to install the [n8n-nodes-mcp](https://github.com/nerding-io/n8n-nodes-mcp)\n\n### Setup\n1. Please make sure to setup n8n locally with MCP Servers by navigating to [n8n-nodes-mcp](https://www.youtube.com/watch?v=NUb73ErUCsA)\n2. Please make sure to install the Bright Data MCP Server [@brightdata/mcp](https://www.npmjs.com/package/@brightdata/mcp)  on your local machine.\n3. Sign up at [Bright Data](https://brightdata.com/).\n4. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel.\n5. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.\n6. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy).\n7. In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below.\n\n![MCPClientAccount.png](fileId:1465)\n\nMake sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token>\n\n### How to customize this workflow to your needs\n\n**Add Scheduled Execution**\n- Add a Cron trigger to run this workflow on a set schedule (e.g., daily/weekly keyword tracking).\n\n**Push Results to Custom Destinations**\n\nConnect output to:\n\n- Google Sheets (for analytics or dashboards)\n\n- PostgreSQL or MySQL DBs (for structured storage)\n\n- Notion or Airtable (for content pipelines)\n\n- Slack or Email (for alerting teams)\n\n\n**Customize Webhook Notifications**\n- Update the Webhook URL in the notification node to push processed results to external APIs, CRMs, or real-time dashboards.\n\n",
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          "type": "n8n-nodes-base.function",
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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;"
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          "type": "n8n-nodes-mcp.mcpClientTool",
          "position": [
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            "toolName": "search_engine",
            "operation": "executeTool",
            "toolParameters": "={\n    \"query\": \"{{ $json.query }}\",\n    \"engine\": \"google\"\n} ",
            "descriptionType": "manual",
            "toolDescription": "Perform a Google Search and Scrape the Google Search Result"
          },
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            "mcpClientApi": {
              "id": "credential-id",
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                  "value": "Bright Data"
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                  "name": "action",
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                  "type": "string",
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            "toolName": "search_engine",
            "operation": "executeTool",
            "toolParameters": "{\n    \"query\": \"{{ $json.query }}\",\n    \"engine\": \"bing\"\n} ",
            "descriptionType": "manual",
            "toolDescription": "Perform a Bing Search and Scrape the Bing Search Result"
          },
          "credentials": {
            "mcpClientApi": {
              "id": "credential-id",
              "name": "mcpClientApi Credential"
            }
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        },
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          "name": "MCP Client for Yandex Search",
          "type": "n8n-nodes-mcp.mcpClientTool",
          "position": [
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          "parameters": {
            "toolName": "search_engine",
            "operation": "executeTool",
            "toolParameters": "{\n    \"query\": \"{{ $json.query }}\",\n    \"engine\": \"yandex\"\n} ",
            "descriptionType": "manual",
            "toolDescription": "Perform a Yandex Search and Scrape the Yandex Search Result"
          },
          "credentials": {
            "mcpClientApi": {
              "id": "credential-id",
              "name": "mcpClientApi Credential"
            }
          },
          "typeVersion": 1
        },
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          "name": "Bright Data Search AI Agent",
          "type": "@n8n/n8n-nodes-langchain.agent",
          "position": [
            -600,
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          ],
          "parameters": {
            "text": "={{ $json.action }}\n\nMake sure to output the response as returned by th specific tool.",
            "options": {},
            "promptType": "define",
            "hasOutputParser": true
          },
          "typeVersion": 2
        },
        {
          "id": "cd255a57-2260-4781-a9b1-e38a4d224572",
          "name": "Google Gemini Chat Model for Search Agent",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
            -900,
            600
          ],
          "parameters": {
            "options": {},
            "modelName": "models/gemini-2.0-flash-exp"
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "51db57ef-8626-4268-b377-cd95021537c8",
          "name": "Write the search result to disk",
          "type": "n8n-nodes-base.readWriteFile",
          "position": [
            420,
            220
          ],
          "parameters": {
            "options": {},
            "fileName": "d:\\Scraped-Search-Results.json",
            "operation": "write"
          },
          "typeVersion": 1
        },
        {
          "id": "afa11162-6e5f-48ee-81a9-120eebf79a72",
          "name": "Webhook for clean data extractor",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
            180,
            420
          ],
          "parameters": {
            "url": "={{ $('Set the Input Fields').item.json.webhook_notification_url }}",
            "options": {},
            "sendBody": true,
            "bodyParameters": {
              "parameters": [
                {
                  "name": "response",
                  "value": "={{ $json.output.search_response }}"
                }
              ]
            }
          },
          "typeVersion": 4.2
        },
        {
          "id": "07ea15dc-d54f-424c-bb75-27054be6996d",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -400,
            140
          ],
          "parameters": {
            "color": 3,
            "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": "8ed88da4-cfd8-4c27-a737-1c718143e1a4",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -860,
            20
          ],
          "parameters": {
            "color": 5,
            "width": 440,
            "height": 240,
            "content": "## LLM Usages\n\nGoogle Gemini LLM is being utilized for the structured data extraction handling."
          },
          "typeVersion": 1
        },
        {
          "id": "b533b59c-5007-4f87-a862-f2765be3d27b",
          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1320,
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          "parameters": {
            "color": 7,
            "width": 440,
            "height": 360,
            "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": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1320,
            -40
          ],
          "parameters": {
            "width": 440,
            "height": 300,
            "content": "## Note\n\nDeals with the Google, Bing, Yandex Search by leveraging the Bright Data MCP Client.\n\n**Please make sure to set the input fields with query, action, Webhook notification URL. Test using https://webhook.site/**\n\nAction - \n1. Perform Google search\n2. Perform Bing search\n3. Perform Yandex search"
          },
          "typeVersion": 1
        },
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          "id": "902a8d8e-d4ad-4934-8c4d-10c7b66aac3c",
          "name": "Human Readable Data Extractor",
          "type": "@n8n/n8n-nodes-langchain.informationExtractor",
          "position": [
            -240,
            300
          ],
          "parameters": {
            "text": "=You are a helpful AI assistant. Given the following search result, return a clean, human-readable information.\n\nRemove any HTML tags, Ignore irrelevant links, ads, navigation text, or footers.\n\nHere's the content -  {{ $json.output }}\n\nImportant - Do not output your own thoughts or suggestions.",
            "options": {},
            "attributes": {
              "attributes": [
                {
                  "name": "search_response",
                  "description": "Search Response"
                }
              ]
            }
          },
          "typeVersion": 1.1
        },
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          "name": "Google Gemini Chat Model for Human Readable Data Extractor",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
            -120,
            500
          ],
          "parameters": {
            "options": {},
            "modelName": "models/gemini-2.0-flash-exp"
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        }
      ],
      "active": false,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
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      "versionId": "0cb1ae5e-f384-48ec-aaa8-e11362a32527",
      "connections": {
        "Create a binary data": {
          "main": [
            [
              {
                "node": "Write the search result to disk",
                "type": "main",
                "index": 0
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          "main": [
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              {
                "node": "Bright Data Search AI Agent",
                "type": "main",
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        },
        "MCP Client for Bing Search": {
          "ai_tool": [
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        "Bright Data Search AI Agent": {
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        "MCP Client for Yandex Search": {
          "ai_tool": [
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                "node": "Bright Data Search AI Agent",
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                "node": "Create a binary data",
                "type": "main",
                "index": 0
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                "node": "Webhook for clean data extractor",
                "type": "main",
                "index": 0
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        },
        "Bright Data MCP Client List Tools": {
          "main": [
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              {
                "node": "Set the Input Fields",
                "type": "main",
                "index": 0
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          ]
        },
        "When clicking ‘Test workflow’": {
          "main": [
            [
              {
                "node": "Bright Data MCP Client List Tools",
                "type": "main",
                "index": 0
              }
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        "Google Gemini Chat Model for Search Agent": {
          "ai_languageModel": [
            [
              {
                "node": "Bright Data Search AI Agent",
                "type": "ai_languageModel",
                "index": 0
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        "Google Gemini Chat Model for Human Readable Data Extractor": {
          "ai_languageModel": [
            [
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                "node": "Human Readable Data Extractor",
                "type": "ai_languageModel",
                "index": 0
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    "status": "published",
    "user": {
      "name": "Ranjan Dailata",
      "username": "ranjancse",
      "bio": "A Professional based out of India specialized in handling AI-powered automations. Contact me at ranjancse@gmail.com ",
      "verified": true,
      "links": [
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            "details": "The Function node allows you to execute JavaScript in your workflow. Unlike the Function Item node, this node does not operate on incoming node data per-item. Instead, you must iterate over multiple items of incoming data yourself. This can be useful if you're performing data transformation where you want to manipulate the number of items being outputted by the node (i.e. 1 item is inputted in with nested object, 10 items are outputted without any nested objects)",
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                  "icon": "store",
                  "label": "6 e-commerce workflows to power up your Shopify s"
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                {
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              "Language Models": [
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            "subcategories": {
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                "Root Nodes"
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            }
          }
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    "categories": [
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        "name": "Market Research"
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        "name": "AI RAG"
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    ],
    "image": [
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    ]
  }
}