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    "name": "Legal Case Research Extractor, Data Miner with Bright Data MCP & Google Gemini",
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    "createdAt": "2025-05-24T04:29:07.388Z",
    "description": "![Legal Case Research Extractor.png](fileId:1376)\n\n### Notice\nCommunity nodes can only be installed on self-hosted instances of n8n.\n\n### Who this is for\nThe Legal Case Research Extractor is a powerful automated workflow designed for legal tech teams, researchers, law firms, and data scientists focused on transforming unstructured legal case data into actionable, structured insights.\n\nThis workflow is tailored for:\n\n- Legal Researchers automating case law data mining\n\n- Litigation Support Teams handling large volumes of case records\n\n- LawTech Startups building AI-powered legal research assistants\n\n- Compliance Analysts extracting case-specific insights\n\n- AI Developers working on legal NLP, summarization, and search engines\n\n### What problem is this workflow solving?\nLegal case data is often locked in semi-structured or raw HTML formats, scattered across jurisdiction-specific websites. Manually extracting and processing this data is tedious and inefficient.\n\nThis workflow automates:\n\n- Extraction of legal case data via Bright Data's powerful MCP infrastructure\n\n- Parsing of HTML into clean, readable text using Google Gemini LLM\n\n- Structuring and delivering the output through webhook and file storage\n\n\n### What this workflow does\n\n**Input**\n\n- Set the Legal Case Research URL node is responsible for setting the legal case URL for the data extraction.\n\n**Bright Data MCP Data Extractor**\n\n- Bright Data MCP Client For Legal Case Research node is responsible for the legal case extraction via the Bright Data MCP tool - scrape_as_html\n\n**Case Extractor**\n\n- Google Gemini based Case Extractor is responsible for producing a paginated list of cases\n\n**Loop through Legal Case URLs**\n\n- Receives a collection of legal case links to process\n\n- Each URL represents a different case from a target legal website\n\n**Bright Data MCP Scraping**\n\n- Utilizes Bright Data’s scrape_as_html MCP mode\n\n- Retrieves raw HTML content of each legal case\n\n**Google Gemini LLM Extraction**\n\n- Transforms raw HTML into clean, structured text\n\n- Performs additional information extraction if required (e.g., case summary, court, jurisdiction etc.)\n\n**Webhook Notification**\n\n- Sends extracted legal case content to a configurable webhook URL\n\n- Enables downstream processing or storage in legal databases\n\n**Binary Conversion & File Persistence**\n\n- Converts the structured text to binary format\n\n- Saves the final response to disk for archival or further processing\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:1375)\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**Target New Legal Portals**\n- Modify the legal case input URLs to scrape from different state or federal case databases\n\n\n**Customize LLM Extraction**\n- Modify the prompt to extract specific fields: case number, plaintiff, case summary, outcome, legal precedents etc.\n\n- Add a summarization step if needed\n\n**Enhance Loop Handling**\n- Integrate with a Google Sheet or API to dynamically fetch case URLs\n\n- Add error handling logic to skip failed cases and log them\n\n**Improve Security & Compliance**\n- Redact sensitive information before sending via webhook\n\n- Store processed case data in encrypted cloud storage\n\n**Output Formats**\n- Save as PDF, JSON, or Markdown\n\n- Enable output to cloud storage (S3, Google Drive) or legal document management systems",
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            "content": "## Bright Data Legal Case Research Scraper"
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            "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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            "content": "## Disclaimer\nThis template is only available on n8n self-hosted as it's making use of the community node for MCP Client."
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                  "type": "string",
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          "notes": "Scrape a single webpage URL with advanced options for content extraction and get back the results in MarkDown language.",
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            "operation": "executeTool",
            "toolParameters": "={\n   \"url\": \"{{ $json.url }}\"\n} "
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            "mcpClientApi": {
              "id": "credential-id",
              "name": "mcpClientApi Credential"
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          "type": "@n8n/n8n-nodes-langchain.chainLlm",
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          "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"
                }
              ]
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            "promptType": "define",
            "hasOutputParser": true
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          "name": "Structured Output Parser",
          "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
          "position": [
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            "jsonSchemaExample": "[{\n\"Id\": \"\",\n\"Link\" : \"\",\n\"Title\": \n\"United States v. IXCOLGONZALEZ\"\n}]"
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          "name": "Bright Data MCP Client For Legal Case Research Within 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": [
            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": "credential-id",
              "name": "mcpClientApi Credential"
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          "name": "HTML to Textual Data Extract Within Loop",
          "type": "@n8n/n8n-nodes-langchain.chainLlm",
          "position": [
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          ],
          "parameters": {
            "text": "=Extract html to textual content  {{ $json.result.content[0].text }}",
            "promptType": "define"
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          "retryOnFail": true,
          "typeVersion": 1.6
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          "type": "n8n-nodes-base.httpRequest",
          "position": [
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            "url": "={{ $('Set the Legal Case Research URL').item.json.webhook_url }}",
            "options": {},
            "sendBody": true,
            "contentType": "multipart-form-data",
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                  "value": "={{ $json.text }}"
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          "parameters": {
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            "fileName": "=d:\\Case-{{ $('Loop Over Items').item.json['Id'] }}.json",
            "operation": "write"
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          "name": "Google Gemini Chat Model For Case Data Extract",
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              "id": "credential-id",
              "name": "googlePalmApi Credential"
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          "name": "Google Gemini Chat Model for HTML to Textual Data Extract Within the Loop",
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            "modelName": "models/gemini-2.0-flash-exp"
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            "content": "## Bright Data Legal Case Research Scraper\n\nLoop through and perform the data extraction using MCP and LLMs"
          },
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          "parameters": {
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            "width": 440,
            "height": 220,
            "content": "## LLM Usages\n\nOpenAI 4o mini LLM is being utilized for the structured data extraction handling."
          },
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        {
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            "width": 400,
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            "content": "## Logo\n\n\n![logo](https://images.seeklogo.com/logo-png/43/1/brightdata-logo-png_seeklogo-439974.png)\n"
          },
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            "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**"
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          "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": 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"
          }
        ]
      },
      {
        "id": 1262,
        "icon": "file:google.svg",
        "name": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatgooglegemini/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Language Models",
                "Root Nodes"
              ],
              "Language Models": [
                "Chat Models (Recommended)"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Google Gemini Chat Model"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Google Gemini Chat Model",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      }
    ],
    "categories": [
      {
        "id": 35,
        "name": "Document Extraction"
      },
      {
        "id": 49,
        "name": "AI Summarization"
      }
    ],
    "image": [
      {
        "id": 1375,
        "url": "https://n8niostorageaccount.blob.core.windows.net/n8nio-strapi-blobs-prod/assets/MCP_Client_Account_8bd93e207b.png"
      },
      {
        "id": 1376,
        "url": "https://n8niostorageaccount.blob.core.windows.net/n8nio-strapi-blobs-prod/assets/Legal_Case_Research_Extractor_f721a381c4.png"
      }
    ]
  }
}