Extractor de estudios de caso legales, minador de datos con Bright Data MCP y Google Gemini

Avanzado

Este es unAI, IT Opsflujo de automatización del dominio deautomatización que contiene 22 nodos.Utiliza principalmente nodos como Set, Code, Wait, Function, McpClient, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Extractor de estudios de caso legales, minero de datos con Bright Data MCP y Google Gemini

Requisitos previos
  • Pueden requerirse credenciales de autenticación para la API de destino
  • Clave de API de Google Gemini
Vista previa del flujo de trabajo
Visualización de las conexiones entre nodos, con soporte para zoom y panorámica
Exportar flujo de trabajo
Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo
{
  "id": "Qgx75aQeRKXKtqm7",
  "meta": {
    "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
    "templateCredsSetupCompleted": true
  },
  "name": "Legal Case Research Extractor, Data Miner with Bright Data MCP & 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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      "name": "Al hacer clic en 'Probar flujo de trabajo'",
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      "parameters": {},
      "typeVersion": 1
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      "name": "Nota adhesiva",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -60,
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      ],
      "parameters": {
        "color": 4,
        "width": 440,
        "height": 320,
        "content": "## Bright Data Legal Case Research Scraper"
      },
      "typeVersion": 1
    },
    {
      "id": "8f1934bf-ccec-4b25-b6cc-7607dcbdf798",
      "name": "Listar todas las herramientas para Bright Data",
      "type": "n8n-nodes-mcp.mcpClient",
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      "parameters": {},
      "credentials": {
        "mcpClientApi": {
          "id": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
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      },
      "typeVersion": 1
    },
    {
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      "name": "Crear datos binarios para extracción de información de la compañía LinkedIn",
      "type": "n8n-nodes-base.function",
      "position": [
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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
    },
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        "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": "048c1093-ea88-441c-98fa-a2d003ab6b8d",
      "name": "Establecer la URL de Investigación de Caso Legal",
      "type": "n8n-nodes-base.set",
      "position": [
        -20,
        140
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "214e61a0-3587-453f-baf5-eac013990857",
              "name": "url",
              "type": "string",
              "value": "https://www.courtlistener.com/?q=IT%20laws%20for%20cyber%20crime&type=o&order_by=dateFiled%20desc&stat_Published=on"
            },
            {
              "id": "45014942-0a2e-4f46-b395-f82f97bfa93e",
              "name": "webhook_url",
              "type": "string",
              "value": "https://webhook.site/7b5380a0-0544-48dc-be43-0116cb2d52c2"
            },
            {
              "id": "bf011e1f-7032-49db-8f25-31ec4c35b9c5",
              "name": "base_url",
              "type": "string",
              "value": "https://www.courtlistener.com"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "8dc0a8cd-e4d9-4252-9dd2-94ee95d698e9",
      "name": "Cliente Bright Data MCP para Investigación de Caso Legal",
      "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": [
        200,
        140
      ],
      "parameters": {
        "toolName": "scrape_as_html",
        "operation": "executeTool",
        "toolParameters": "={\n   \"url\": \"{{ $json.url }}\"\n} "
      },
      "credentials": {
        "mcpClientApi": {
          "id": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
        }
      },
      "notesInFlow": true,
      "typeVersion": 1
    },
    {
      "id": "f3ea0d19-703b-4f99-955c-122162065363",
      "name": "Extractor de Casos",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
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        140
      ],
      "parameters": {
        "text": "=Extract the content in a structured format. Here's the content : {{ $json.result.content[0].text }}",
        "messages": {
          "messageValues": [
            {
              "message": "You are an expert structured data extractor"
            }
          ]
        },
        "promptType": "define",
        "hasOutputParser": true
      },
      "retryOnFail": true,
      "typeVersion": 1.6
    },
    {
      "id": "a3fe5ce7-3a91-459d-8ef8-17a06fbef12a",
      "name": "Analizador de Salida Estructurada",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        800,
        360
      ],
      "parameters": {
        "jsonSchemaExample": "[{\n\"Id\": \"\",\n\"Link\" : \"\",\n\"Title\": \n\"United States v. IXCOLGONZALEZ\"\n}]"
      },
      "typeVersion": 1.2
    },
    {
      "id": "5fd6d0a3-46ca-4184-bc5c-dfc0966f0538",
      "name": "Iterar sobre Elementos",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
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      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 3
    },
    {
      "id": "74a02ac0-859d-4611-aeb0-021a654c92b8",
      "name": "Cliente Bright Data MCP para Investigación de Caso Legal dentro del Bucle",
      "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": [
        1860,
        160
      ],
      "parameters": {
        "toolName": "scrape_as_html",
        "operation": "executeTool",
        "toolParameters": "={\n   \"url\": \"{{ $('Set the Legal Case Research URL').item.json.base_url }}/{{ $json.Link }}\"\n} "
      },
      "credentials": {
        "mcpClientApi": {
          "id": "JtatFSfA2kkwctYa",
          "name": "MCP Client (STDIO) account"
        }
      },
      "notesInFlow": true,
      "typeVersion": 1
    },
    {
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      "name": "Extraer HTML a Datos Textuales dentro del Bucle",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        2080,
        160
      ],
      "parameters": {
        "text": "=Extract html to textual content  {{ $json.result.content[0].text }}",
        "promptType": "define"
      },
      "retryOnFail": true,
      "typeVersion": 1.6
    },
    {
      "id": "b7fc74e5-4165-4b1a-9c0a-27565302c0e1",
      "name": "Notificación Webhook para Extracción de HTML a Datos Textuales dentro del Bucle",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        2440,
        260
      ],
      "parameters": {
        "url": "={{ $('Set the Legal Case Research URL').item.json.webhook_url }}",
        "options": {},
        "sendBody": true,
        "contentType": "multipart-form-data",
        "bodyParameters": {
          "parameters": [
            {
              "name": "case_content",
              "value": "={{ $json.text }}"
            }
          ]
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "07b78de1-fdc8-4233-a231-37258fa5d1f0",
      "name": "Escribir el contenido del caso en disco",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        2700,
        60
      ],
      "parameters": {
        "options": {},
        "fileName": "=d:\\Case-{{ $('Loop Over Items').item.json['Id'] }}.json",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "ff687082-9e3d-4043-9aa6-29e3029499d4",
      "name": "Modelo de Chat Google Gemini para Extracción de Datos del Caso",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
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        360
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "0057d772-732e-4e47-8ab8-eebe140df692",
      "name": "Código para generar la colección de casos",
      "type": "n8n-nodes-base.code",
      "position": [
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      ],
      "parameters": {
        "jsCode": "\nreturn $input.first().json.output"
      },
      "typeVersion": 2
    },
    {
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      "name": "Modelo de Chat Google Gemini para Extracción de HTML a Datos Textuales dentro del Bucle",
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      "position": [
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      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
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      "name": "Nota adhesiva1",
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      "position": [
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      ],
      "parameters": {
        "color": 5,
        "width": 1660,
        "height": 520,
        "content": "## Bright Data Legal Case Research Scraper\n\nLoop through and perform the data extraction using MCP and LLMs"
      },
      "typeVersion": 1
    },
    {
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      "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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      "position": [
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      "parameters": {
        "width": 400,
        "height": 320,
        "content": "## Note\n\nDeals with the Legal Case 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 Legal case URL\n\nPlease make sure to update the Webhook Notification URL of your interest**"
      },
      "typeVersion": 1
    },
    {
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      "name": "Esperar",
      "type": "n8n-nodes-base.wait",
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      ],
      "webhookId": "65c9fcd3-2c82-4bdd-80b6-271d65b7f61a",
      "parameters": {
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}
Preguntas frecuentes

¿Cómo usar este flujo de trabajo?

Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.

¿En qué escenarios es adecuado este flujo de trabajo?

Avanzado - Inteligencia Artificial, Operaciones de TI

¿Es de pago?

Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.

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Información del flujo de trabajo
Nivel de dificultad
Avanzado
Número de nodos22
Categoría2
Tipos de nodos13
Descripción de la dificultad

Adecuado para usuarios avanzados, flujos de trabajo complejos con 16+ nodos

Autor
Ranjan Dailata

Ranjan Dailata

@ranjancse

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

Enlaces externos
Ver en n8n.io

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Categorías

Categorías: 34