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使用 Bright Data MCP Agent 和 Google Gemini 执行 Google、Bing、Yandex 搜索

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这是一个AI, Marketing领域的自动化工作流,包含 17 个节点。主要使用 Set, Function, McpClient, HttpRequest, McpClientTool 等节点,结合人工智能技术实现智能自动化。 使用 Bright Data MCP 和 Google Gemini 搜索 Google、Bing、Yandex 并提取结构化结果

前置要求
  • 可能需要目标 API 的认证凭证
  • Google Gemini API Key
工作流预览
可视化展示节点连接关系,支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入,即可使用此工作流
{
  "id": "XSN9T4R0IyqcV2gC",
  "meta": {
    "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
    "templateCredsSetupCompleted": true
  },
  "name": "使用 Bright Data MCP Agent 和 Google Gemini 执行 Google、Bing、Yandex 搜索",
  "tags": [
    {
      "id": "Kujft2FOjmOVQAmJ",
      "name": "Engineering",
      "createdAt": "2025-04-09T01:31:00.558Z",
      "updatedAt": "2025-04-09T01:31:00.558Z"
    },
    {
      "id": "ZOwtAMLepQaGW76t",
      "name": "Building Blocks",
      "createdAt": "2025-04-13T15:23:40.462Z",
      "updatedAt": "2025-04-13T15:23:40.462Z"
    },
    {
      "id": "ddPkw7Hg5dZhQu2w",
      "name": "AI",
      "createdAt": "2025-04-13T05:38:08.053Z",
      "updatedAt": "2025-04-13T05:38:08.053Z"
    }
  ],
  "nodes": [
    {
      "id": "80b9e843-974a-4a93-871f-3ead444d1757",
      "name": "当点击\"测试工作流\"时",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -1300,
        300
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "2debe6c6-80ef-4fba-a40d-fcfd8a09eefa",
      "name": "Bright Data MCP 客户端列表工具",
      "type": "n8n-nodes-mcp.mcpClient",
      "position": [
        -1080,
        300
      ],
      "parameters": {},
      "credentials": {
        "mcpClientApi": {
          "id": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0b66f5bb-66bb-41cf-b165-552d5b169dce",
      "name": "创建二进制数据",
      "type": "n8n-nodes-base.function",
      "position": [
        180,
        220
      ],
      "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": "8516c6d6-fcae-42ab-8921-9f1d5500f73b",
      "name": "Google 搜索的 MCP 客户端",
      "type": "n8n-nodes-mcp.mcpClientTool",
      "position": [
        -720,
        600
      ],
      "parameters": {
        "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"
      },
      "credentials": {
        "mcpClientApi": {
          "id": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "a17ff821-c508-4b61-8d35-e7f1580e5bb1",
      "name": "设置输入字段",
      "type": "n8n-nodes-base.set",
      "position": [
        -860,
        300
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "219c5e66-e167-44c3-bc65-612c70e8d4a1",
              "name": "query",
              "type": "string",
              "value": "Bright Data"
            },
            {
              "id": "2b9b0541-5c5e-446f-aeaf-8c9ce00dfa00",
              "name": "action",
              "type": "string",
              "value": "Perform Bing search"
            },
            {
              "id": "bcc3ce2a-3708-4b6f-8ddd-3b5e611c63d0",
              "name": "webhook_notification_url",
              "type": "string",
              "value": "https://webhook.site/c9118da2-1c54-460f-a83a-e5131b7098db"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "42639030-338c-4d30-a2e0-a5aaa9325191",
      "name": "用于 Bing 搜索的 MCP 客户端",
      "type": "n8n-nodes-mcp.mcpClientTool",
      "position": [
        -500,
        600
      ],
      "parameters": {
        "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": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "18f1374e-2516-481c-9fed-3c8757a21296",
      "name": "用于 Yandex 搜索的 MCP 客户端",
      "type": "n8n-nodes-mcp.mcpClientTool",
      "position": [
        -300,
        600
      ],
      "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": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "ff15f988-5f23-4a22-b2fb-25bdd558fce4",
      "name": "Bright Data 搜索 AI 代理",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -600,
        300
      ],
      "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": "用于搜索代理的 Google Gemini 聊天模型",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        -900,
        600
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "51db57ef-8626-4268-b377-cd95021537c8",
      "name": "将搜索结果写入磁盘",
      "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": "用于干净数据提取的 Webhook",
      "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": "便签 2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -400,
        140
      ],
      "parameters": {
        "color": 3,
        "width": 440,
        "height": 120,
        "content": "## 免责声明"
      },
      "typeVersion": 1
    },
    {
      "id": "8ed88da4-cfd8-4c27-a737-1c718143e1a4",
      "name": "便签 4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -860,
        20
      ],
      "parameters": {
        "color": 5,
        "width": 440,
        "height": 240,
        "content": "## LLM 使用情况"
      },
      "typeVersion": 1
    },
    {
      "id": "b533b59c-5007-4f87-a862-f2765be3d27b",
      "name": "便签 5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1320,
        -420
      ],
      "parameters": {
        "color": 7,
        "width": 440,
        "height": 360,
        "content": "## 徽标"
      },
      "typeVersion": 1
    },
    {
      "id": "17265f2a-5224-498c-bf50-36b87a1c3b22",
      "name": "便签 3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1320,
        -40
      ],
      "parameters": {
        "width": 440,
        "height": 300,
        "content": "## 注意"
      },
      "typeVersion": 1
    },
    {
      "id": "902a8d8e-d4ad-4934-8c4d-10c7b66aac3c",
      "name": "人类可读数据提取器",
      "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
    },
    {
      "id": "1eca092e-da55-4025-85d1-d1d715e23f83",
      "name": "用于人类可读数据提取器的 Google Gemini 聊天模型",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        -120,
        500
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "0cb1ae5e-f384-48ec-aaa8-e11362a32527",
  "connections": {
    "Create a binary data": {
      "main": [
        [
          {
            "node": "Write the search result to disk",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set the Input Fields": {
      "main": [
        [
          {
            "node": "Bright Data Search AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "MCP Client for Bing Search": {
      "ai_tool": [
        [
          {
            "node": "Bright Data Search AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Bright Data Search AI Agent": {
      "main": [
        [
          {
            "node": "Human Readable Data Extractor",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "MCP Client for Google Search": {
      "ai_tool": [
        [
          {
            "node": "Bright Data Search AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "MCP Client for Yandex Search": {
      "ai_tool": [
        [
          {
            "node": "Bright Data Search AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Human Readable Data Extractor": {
      "main": [
        [
          {
            "node": "Create a binary data",
            "type": "main",
            "index": 0
          },
          {
            "node": "Webhook for clean data extractor",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Bright Data MCP Client List Tools": {
      "main": [
        [
          {
            "node": "Set the Input Fields",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking ‘Test workflow’": {
      "main": [
        [
          {
            "node": "Bright Data MCP Client List Tools",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model for Search Agent": {
      "ai_languageModel": [
        [
          {
            "node": "Bright Data Search AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model for Human Readable Data Extractor": {
      "ai_languageModel": [
        [
          {
            "node": "Human Readable Data Extractor",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}
常见问题

如何使用这个工作流?

复制上方的 JSON 配置代码,在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」,粘贴配置后根据需要修改凭证设置即可。

这个工作流适合什么场景?

高级 - 人工智能, 营销

需要付费吗?

本工作流完全免费,您可以直接导入使用。但请注意,工作流中使用的第三方服务(如 OpenAI API)可能需要您自行付费。

工作流信息
难度等级
高级
节点数量17
分类2
节点类型11
难度说明

适合高级用户,包含 16+ 个节点的复杂工作流

作者
Ranjan Dailata

Ranjan Dailata

@ranjancse

A Professional based out of India specialized in handling AI-powered automations. Contact me at ranjancse@gmail.com

外部链接
在 n8n.io 查看

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