Extracteur d'études de cas juridiques, Mineur de données avec Bright Data MCP et Google Gemini
Avancé
Ceci est unAI, IT Opsworkflow d'automatisation du domainecontenant 22 nœuds.Utilise principalement des nœuds comme Set, Code, Wait, Function, McpClient, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Extracteur d'études de cas juridiques, mineur de données utilisant Bright Data MCP et Google Gemini
Prérequis
- •Peut nécessiter les informations d'identification d'authentification de l'API cible
- •Clé API Google Gemini
Nœuds utilisés (22)
Aperçu du workflow
Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement
Exporter le workflow
Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow
{
"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"
}
],
"nodes": [
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"id": "9e9a27ce-b95c-4ecd-b3c4-97aba420ce45",
"name": "Lors du clic sur 'Tester le workflow'",
"type": "n8n-nodes-base.manualTrigger",
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"parameters": {},
"typeVersion": 1
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{
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"name": "Note autocollante",
"type": "n8n-nodes-base.stickyNote",
"position": [
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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": "Lister tous les outils pour Bright Data",
"type": "n8n-nodes-mcp.mcpClient",
"position": [
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"parameters": {},
"credentials": {
"mcpClientApi": {
"id": "JtatFSfA2kkwctYa",
"name": "MCP Client (STDIO) account"
}
},
"typeVersion": 1
},
{
"id": "f8c4804a-85ad-462c-913d-e0bc5242bc74",
"name": "Créer des données binaires pour l'extraction d'informations de l'entreprise 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
},
{
"id": "c616db9f-fcf3-4f9d-b60f-a16c9da89456",
"name": "Note autocollante2",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"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": "048c1093-ea88-441c-98fa-a2d003ab6b8d",
"name": "Définir l'URL de Recherche de Cas Juridique",
"type": "n8n-nodes-base.set",
"position": [
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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": "Client MCP Bright Data pour la Recherche de Cas Juridique",
"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": "Extracteur de Cas",
"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": "Analyseur de Sortie Structurée",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
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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": "Boucle sur les Éléments",
"type": "n8n-nodes-base.splitInBatches",
"position": [
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],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "74a02ac0-859d-4611-aeb0-021a654c92b8",
"name": "Client MCP Bright Data pour la Recherche de Cas Juridique dans la Boucle",
"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
},
{
"id": "beb67c30-dd39-4c7d-94f8-853410dec09b",
"name": "Extraction de Données Textuelles depuis HTML dans la Boucle",
"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": "Notification Webhook pour l'Extraction de Données Textuelles depuis HTML dans la Boucle",
"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": "Écrire le contenu du cas sur le disque",
"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": "Modèle de Chat Google Gemini pour l'Extraction de Données de Cas",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
580,
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": "Code pour sortir la collection de cas",
"type": "n8n-nodes-base.code",
"position": [
980,
140
],
"parameters": {
"jsCode": "\nreturn $input.first().json.output"
},
"typeVersion": 2
},
{
"id": "c843170b-e360-4eea-853c-ef38c9f3affe",
"name": "Modèle de Chat Google Gemini pour l'Extraction de Données Textuelles depuis HTML dans la Boucle",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"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": "Note autocollante1",
"type": "n8n-nodes-base.stickyNote",
"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
},
{
"id": "58aac68b-2598-465b-ab3c-f5c0ebcdb595",
"name": "Note autocollante4",
"type": "n8n-nodes-base.stickyNote",
"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
},
{
"id": "14bbbc73-06cd-4513-b9e6-2aebb5009c3d",
"name": "Note autocollante5",
"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"color": 7,
"width": 400,
"height": 400,
"content": "## Logo\n\n\n\n"
},
"typeVersion": 1
},
{
"id": "96d74c50-074e-4b83-9422-ff2ce56bd55d",
"name": "Note autocollante3",
"type": "n8n-nodes-base.stickyNote",
"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
},
{
"id": "08c6a217-5773-4ebc-ba6e-326de99e90e5",
"name": "Attente",
"type": "n8n-nodes-base.wait",
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"webhookId": "65c9fcd3-2c82-4bdd-80b6-271d65b7f61a",
"parameters": {
"amount": 10
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],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
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"versionId": "03af01f8-7276-4c3c-a610-6532f0d51ef7",
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"type": "main",
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"0057d772-732e-4e47-8ab8-eebe140df692": {
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"ff687082-9e3d-4043-9aa6-29e3029499d4": {
"ai_languageModel": [
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"type": "ai_languageModel",
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}
}Foire aux questions
Comment utiliser ce workflow ?
Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.
Dans quelles scénarios ce workflow est-il adapté ?
Avancé - Intelligence Artificielle, Opérations IT
Est-ce payant ?
Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.
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Informations sur le workflow
Niveau de difficulté
Avancé
Nombre de nœuds22
Catégorie2
Types de nœuds13
Description de la difficulté
Auteur
Ranjan Dailata
@ranjancseA Professional based out of India specialized in handling AI-powered automations. Contact me at ranjancse@gmail.com
Liens externes
Voir sur n8n.io →
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