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LinkedIn-Web Scraping mit Bright Data MCP-Server und Google Gemini

Experte

Dies ist ein AI, Marketing, IT Ops-Bereich Automatisierungsworkflow mit 20 Nodes. Hauptsächlich werden Set, Code, Merge, Function, McpClient und andere Nodes verwendet, kombiniert mit KI-Technologie für intelligente Automatisierung. Extrahieren und Konvertieren von LinkedIn-Daten mit Bright Data MCP Server und Google Gemini

Voraussetzungen
  • •Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
  • •Google Gemini API Key

Verwendete Nodes (20)

Set
Code
Merge
Function
McpClient
Aggregate
StickyNote
HttpRequest
ManualTrigger
ReadWriteFile
LmChatGoogleGemini
InformationExtractor

Kategorie

Künstliche Intelligenz
Marketing
IT-Betrieb
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
React Flow
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
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  "meta": {
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    "templateCredsSetupCompleted": true
  },
  "name": "LinkedIn Web Scraping with Bright Data MCP Server & Google Gemini",
  "tags": [
    {
      "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"
    }
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  "nodes": [
    {
      "id": "68715d64-ce99-4e23-81ed-fe8f7d08ebd7",
      "name": "Bei Klick auf 'Workflow testen'",
      "type": "n8n-nodes-base.manualTrigger",
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      "parameters": {},
      "typeVersion": 1
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    {
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      "position": [
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      ],
      "parameters": {
        "color": 3,
        "width": 440,
        "height": 320,
        "content": "## Bright Data LinkedIn Person Scraper"
      },
      "typeVersion": 1
    },
    {
      "id": "cdf42164-569e-4140-9847-4751d69c6b7b",
      "name": "URLs festlegen",
      "type": "n8n-nodes-base.set",
      "position": [
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        "options": {},
        "assignments": {
          "assignments": [
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              "name": "url",
              "type": "string",
              "value": "https://www.linkedin.com/in/ranjan-dailata/"
            },
            {
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              "name": "webhook_url",
              "type": "string",
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    {
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      "name": "Bright Data MCP Client für LinkedIn Person",
      "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": [
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      "parameters": {
        "toolName": "web_data_linkedin_person_profile",
        "operation": "executeTool",
        "toolParameters": "={\n   \"url\": \"{{ $json.url }}\"\n} "
      },
      "credentials": {
        "mcpClientApi": {
          "id": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
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      "parameters": {
        "color": 4,
        "width": 440,
        "height": 320,
        "content": "## Bright Data LinkedIn Company Scraper"
      },
      "typeVersion": 1
    },
    {
      "id": "69afab25-32c6-4849-b2f9-4a2b25657c37",
      "name": "Alle Tools für Bright Data auflisten",
      "type": "n8n-nodes-mcp.mcpClient",
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      "parameters": {},
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    {
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      "name": "Bright Data MCP Client für LinkedIn Company",
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      "notes": "Scrape a single webpage URL with advanced options for content extraction and get back the results in MarkDown language.",
      "position": [
        20,
        50
      ],
      "parameters": {
        "toolName": "web_data_linkedin_company_profile",
        "operation": "executeTool",
        "toolParameters": "={\n   \"url\": \"{{ $json.url }}\"\n} "
      },
      "credentials": {
        "mcpClientApi": {
          "id": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
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      "notesInFlow": true,
      "typeVersion": 1
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    {
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            {
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              "name": "webhook_url",
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      },
      "typeVersion": 3.4
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    {
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      "name": "Webhook für LinkedIn Company Web Scraper",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
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      ],
      "parameters": {
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        "options": {},
        "jsonBody": "={\n  \"about\": {{ JSON.stringify($json.about[0]) }},\n \"story\": {{ JSON.stringify($json.company_story[0]) }}\n}",
        "sendBody": true,
        "specifyBody": "json"
      },
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    {
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      "parameters": {
        "text": "=Write a complete story of the provided company information in JSON. Use the following Company info to produce a story or a blog post. Make sure to incorporate all the provided company context.\n\nHere's the Company Info in JSON - {{ $json.input }}",
        "options": {
          "systemPromptTemplate": "You are an expert data formatter"
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        "attributes": {
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            {
              "name": "company_story",
              "required": true,
              "description": "Detailed Company Info"
            }
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      },
      "typeVersion": 1
    },
    {
      "id": "d1927c08-5ded-4b0b-b60b-bed126040d38",
      "name": "Google Gemini Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        328,
        420
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0de1d200-c35a-41df-b512-8b97b92f14db",
      "name": "Alle verfügbaren Tools für Bright Data auflisten",
      "type": "n8n-nodes-mcp.mcpClient",
      "position": [
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        }
      },
      "typeVersion": 1
    },
    {
      "id": "3f884694-b8f3-478a-b1a3-f46326a0c96f",
      "name": "Code",
      "type": "n8n-nodes-base.code",
      "position": [
        318,
        -100
      ],
      "parameters": {
        "jsCode": "jsonContent = JSON.parse($input.first().json.result.content[0].text) \nreturn jsonContent\n"
      },
      "typeVersion": 2
    },
    {
      "id": "67036198-4d7d-42d9-93cf-ffc65649bae0",
      "name": "Zusammenführen",
      "type": "n8n-nodes-base.merge",
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      "parameters": {},
      "typeVersion": 3.1
    },
    {
      "id": "77423290-bd08-4dc8-9f37-cf8fec9f6a63",
      "name": "Aggregieren",
      "type": "n8n-nodes-base.aggregate",
      "position": [
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      "parameters": {
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        "fieldsToAggregate": {
          "fieldToAggregate": [
            {
              "fieldToAggregate": "about"
            },
            {
              "fieldToAggregate": "output.company_story"
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      },
      "typeVersion": 1
    },
    {
      "id": "91d25405-afb3-4ed6-b8fa-52ab64a654e2",
      "name": "Binärdaten für LinkedIn Personenextraktion erstellen",
      "type": "n8n-nodes-base.function",
      "position": [
        320,
        -500
      ],
      "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": "3e74c49e-eb31-43b1-b8e1-ed960bd83ca1",
      "name": "LinkedIn Personeninfo auf Festplatte speichern",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        520,
        -500
      ],
      "parameters": {
        "options": {},
        "fileName": "d:\\LinkedIn-Person.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "f92b3505-2af6-42aa-bf4b-8b7b6cb97364",
      "name": "Binärdaten für LinkedIn Firmenextraktion erstellen",
      "type": "n8n-nodes-base.function",
      "position": [
        1000,
        -180
      ],
      "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": "6ed1402b-4858-4311-bede-f0b8f28acb9f",
      "name": "LinkedIn Firmeninfo auf Festplatte speichern",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        1220,
        -180
      ],
      "parameters": {
        "options": {},
        "fileName": "d:\\LinkedIn-Company.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "335efc2b-80e3-4fac-b31f-82fff4ac4e65",
      "name": "Webhook für LinkedIn Person Web Scraper",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        318,
        -300
      ],
      "parameters": {
        "url": "={{ $('Set the URLs').item.json.webhook_url }}",
        "options": {},
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "response",
              "value": "={{ $json.result.content[0].text }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
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}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Experte - Künstliche Intelligenz, Marketing, IT-Betrieb

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

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Node-Typen12
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Autor
Ranjan Dailata

Ranjan Dailata

@ranjancse
Externe Links
Auf n8n.io ansehen →

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Kategorien

Multimodales KI
1540
Künstliche Intelligenz
1108
Content-Erstellung
695
KI-Zusammenfassung
516
Marketing
419
KI-Chatbot
251
Engineering
241
Marktforschung
203
Verschiedenes
193
Sonstiges
176
Vertrieb
162
IT-Betrieb
156
Dokumentenextraktion
147
KI RAG
146
Bausteine
144
Soziale Medien
137
Lead-Generierung
125
Persönliche Produktivität
117
DevOps
111
Personalwesen
101
Support
97
Lead-Pflege
87
Kundenbeziehungsmanagement
82
Finanzen
81
Produkt
77
Support-Chatbot
76
Design
70
Ticketverwaltung
67
Sicherheitsbetrieb
57
Rechnungsverarbeitung
53
Krypto-Handel
49
Dateiverwaltung
39
Projektmanagement
35
Internes Wiki
32

Kategorien: 34