Ranjan Dailata 
This workflow corresponds to n8n.io template #4611 — we link there as the canonical source.
This workflow follows the Chainllm → Chainsummarization recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "L6nGDqfxvxzlvDU2",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Extract, Summarize, Sentiment Analysis of Price Drops for Amazon Products via Bright Data",
"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": "c05c50b0-410e-428c-b9b9-c300b95b0ce8",
"name": "When clicking \u2018Test workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-760,
-595
],
"parameters": {},
"typeVersion": 1
},
{
"id": "e2bef95f-a42a-47f1-b49f-1e18a7a76fc5",
"name": "Bright Data MCP Client List Tools",
"type": "n8n-nodes-mcp.mcpClient",
"position": [
-540,
-595
],
"parameters": {},
"credentials": {
"mcpClientApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "03126e8e-b3ef-4bc1-966f-23050034e717",
"name": "Set input fields",
"type": "n8n-nodes-base.set",
"position": [
-320,
-595
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "0ac91db2-9848-40d4-b942-cd7288597ded",
"name": "price_drop_url",
"type": "string",
"value": "https://camelcamelcamel.com/top_drops?t=daily"
},
{
"id": "88826650-2a6f-4d19-8a2f-27b039296a00",
"name": "webhook_notification_url",
"type": "string",
"value": "https://webhook.site/24878284-919d-4d39-bff0-5f36bfae17b6"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "bb47435e-750a-4767-85bc-8eb1d6af2bc7",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
160,
-780
],
"parameters": {
"color": 3,
"width": 440,
"height": 140,
"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": "377c7b92-4660-4130-a668-40752a52705a",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-300,
-880
],
"parameters": {
"color": 5,
"width": 440,
"height": 240,
"content": "## LLM Usages\n\nGoogle Gemini LLM is being utilized for the structured data extraction handling."
},
"typeVersion": 1
},
{
"id": "45f786b2-e785-4da5-af17-cd048bc93887",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-760,
-1280
],
"parameters": {
"color": 7,
"width": 440,
"height": 360,
"content": "## Logo\n\n\n\n"
},
"typeVersion": 1
},
{
"id": "83d52f24-3c6e-4640-9e95-e41c6c9cfa37",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-760,
-880
],
"parameters": {
"width": 440,
"height": 240,
"content": "## Note\n\nDeals with the extraction of price drop information of ecommerce produce and scraping the site by leveraging the Bright Data MCP Client.\n\nThis workflow is also responsible for the structured data extraction, sentiment analysis and summarization of content.\n\n**Please make sure to set the input fields**"
},
"typeVersion": 1
},
{
"id": "b0b39697-10e6-4066-8122-40775bb1472b",
"name": "Split Out",
"type": "n8n-nodes-base.splitOut",
"position": [
496,
-595
],
"parameters": {
"options": {},
"fieldToSplitOut": "output"
},
"typeVersion": 1
},
{
"id": "d73bf29c-b80c-47c4-b162-60a53bd4e0e0",
"name": "Loop Over Items",
"type": "n8n-nodes-base.splitInBatches",
"position": [
716,
-595
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "c6e5c79a-2a5b-40ae-a0e5-188d35f75c39",
"name": "Wait",
"type": "n8n-nodes-base.wait",
"position": [
936,
-770
],
"parameters": {
"amount": 10
},
"typeVersion": 1.1
},
{
"id": "fa7525b9-86b0-4646-994f-38b85a00f0d9",
"name": "Summarize Content",
"type": "@n8n/n8n-nodes-langchain.chainSummarization",
"position": [
1376,
-1120
],
"parameters": {
"options": {},
"chunkingMode": "advanced"
},
"retryOnFail": true,
"typeVersion": 2.1
},
{
"id": "1f6dd841-144f-44a7-9220-fd7aaf2090bd",
"name": "Sentiment Analysis",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
1376,
-620
],
"parameters": {
"text": "=Perform sentiment analysis of {{ $json.result.content[0].text }}",
"options": {},
"schemaType": "manual",
"inputSchema": "{\n \"$schema\": \"http://json-schema.org/schema#\",\n \"title\": \"EcommerceSentimentSubset\",\n \"type\": \"object\",\n \"properties\": {\n \"sentiment\": {\n \"type\": \"string\",\n \"enum\": [\"positive\", \"neutral\", \"negative\"],\n \"description\": \"Categorized sentiment from NLP analysis\"\n },\n \"sentimentScore\": {\n \"type\": \"number\",\n \"minimum\": -1,\n \"maximum\": 1,\n \"description\": \"Numeric sentiment polarity score (-1 = very negative, 1 = very positive)\"\n },\n \"topics\": {\n \"type\": \"array\",\n \"description\": \"Key aspects mentioned in the review (e.g., battery, build quality, delivery)\",\n \"items\": {\n \"type\": \"string\"\n }\n }\n }\n}\n"
},
"retryOnFail": true,
"typeVersion": 1.1
},
{
"id": "db2330d2-2490-4822-b5c5-519fecb95c1d",
"name": "Google Gemini Chat Model for Summarize Content",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1380,
-900
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "b887a1a5-4de1-43bb-b51c-fd218d5ca2e6",
"name": "Google Gemini Chat Model for Sentiment Analysis",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1464,
-400
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "e14757c2-3457-445b-9acf-5391de2d61fc",
"name": "Merge",
"type": "n8n-nodes-base.merge",
"position": [
1752,
-770
],
"parameters": {},
"typeVersion": 3.1
},
{
"id": "fc1dc2fd-e407-4e7c-acf8-5d29ebb18956",
"name": "Update Google Sheets",
"type": "n8n-nodes-base.googleSheets",
"position": [
2192,
-520
],
"parameters": {
"columns": {
"value": {
"output": "={{ $json.data.toJsonString() }}"
},
"schema": [
{
"id": "output",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "output",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"output"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/10gAihQMT8-h8Mpehe9j-xxN4oTTpg8qwToI-I-Eauew/edit#gid=0",
"cachedResultName": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1a1yb4XSMQ0Vs0Rg2RCwrcIVXwDN3ImXW_4OUebURKZI",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1a1yb4XSMQ0Vs0Rg2RCwrcIVXwDN3ImXW_4OUebURKZI/edit?usp=drivesdk",
"cachedResultName": "Pricedrop Info"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.5
},
{
"id": "65f7cc8e-7776-4712-b131-bc8374fbce20",
"name": "Webhook Notification for Price Drop Info",
"type": "n8n-nodes-base.httpRequest",
"position": [
2192,
-770
],
"parameters": {
"url": "={{ $('Set input fields').item.json.webhook_notification_url }}",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "response",
"value": "={{ $json.data.toJsonString() }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "707977ff-cdfb-4020-86f4-5d0be44ee52f",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
100,
-360
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "bbc02162-176f-4131-9f63-d5e39fb52b9b",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
320,
-360
],
"parameters": {
"jsonSchemaExample": "[{\n\"id\": \"unique_id\",\n\"title\": \n\"Atosa MBF8005GR 52\u2033 Reach-In Refrigerator for Restaurant Deli Cafeteria Steak House | Top Mount Compressor, 43.2 Cu. Ft. | 2-Solid Swing Door, 6 Adjustable Epoxy Coated Shelves | Stainless Steel, 115v\",\n\"price\": \n\"$2,919.48\",\n\"savings\": \n\"Save 18% ($649.36)\",\n\"link\": \n\"https://camelcamelcamel.com/product/07BH0Y75B4KUYI1YP78IB/go?context=top%5Fdrops&ctx%5Fpid=94751977&ctx%5Fcid=-1&ctx%5Faid=-1&ctx%5Fact=buy&ctx%5Fsrc=buy-button&&sjc=1\"\n}]"
},
"typeVersion": 1.2
},
{
"id": "fd27eb98-e1ec-4747-9aeb-c0bf491e057a",
"name": "Structure Data Extract Using LLM",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
120,
-595
],
"parameters": {
"text": "=Extract structured data from {{ $json.result.content[0].text }}",
"batching": {},
"promptType": "define",
"hasOutputParser": true
},
"retryOnFail": true,
"typeVersion": 1.7
},
{
"id": "6a0bc566-2eb8-4eea-bf11-d040f352fbf7",
"name": "MCP Client for Price Drop Data Extract",
"type": "n8n-nodes-mcp.mcpClient",
"position": [
-100,
-595
],
"parameters": {
"toolName": "scrape_as_markdown",
"operation": "executeTool",
"toolParameters": "={\n \"url\": \"{{ $json.price_drop_url }}\"\n} "
},
"credentials": {
"mcpClientApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "22d7cba2-5d8f-4e2a-8d99-e1dd2b232fd3",
"name": "MCP Client for Price Drop Data Extract Within a Loop",
"type": "n8n-nodes-mcp.mcpClient",
"position": [
1156,
-770
],
"parameters": {
"toolName": "scrape_as_markdown",
"operation": "executeTool",
"toolParameters": "={\n \"url\": \"{{ $json.link }}\"\n} "
},
"credentials": {
"mcpClientApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "1ccf68b1-ab0c-4288-8892-f6736639f952",
"name": "Aggregate",
"type": "n8n-nodes-base.aggregate",
"position": [
1972,
-770
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "cf8bdb20-18e5-4d29-b582-65b2b9c7aa32",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
1580,
-900
],
"parameters": {
"options": {},
"chunkSize": 5000
},
"typeVersion": 1
},
{
"id": "3207d699-e620-4324-b71e-29aec2ffaf9a",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
1880,
-860
],
"parameters": {
"color": 5,
"width": 560,
"height": 640,
"content": "## Output Data Handling "
},
"typeVersion": 1
},
{
"id": "26874b27-2d9e-4564-ade2-87f236b250e0",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
-1200
],
"parameters": {
"color": 4,
"width": 1080,
"height": 980,
"content": "## Loop and Extract Data\n\nPerform Summarization & Sentiment Analysis"
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "c9e4ce77-7ccb-47dd-90b8-e9b45036ca5e",
"connections": {
"Wait": {
"main": [
[
{
"node": "MCP Client for Price Drop Data Extract Within a Loop",
"type": "main",
"index": 0
}
]
]
},
"Merge": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Update Google Sheets",
"type": "main",
"index": 0
},
{
"node": "Webhook Notification for Price Drop Info",
"type": "main",
"index": 0
}
]
]
},
"Split Out": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[],
[
{
"node": "Wait",
"type": "main",
"index": 0
}
]
]
},
"Set input fields": {
"main": [
[
{
"node": "MCP Client for Price Drop Data Extract",
"type": "main",
"index": 0
}
]
]
},
"Summarize Content": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 0
}
]
]
},
"Sentiment Analysis": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"Update Google Sheets": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Structure Data Extract Using LLM",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Structure Data Extract Using LLM",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Structure Data Extract Using LLM": {
"main": [
[
{
"node": "Split Out",
"type": "main",
"index": 0
}
]
]
},
"Bright Data MCP Client List Tools": {
"main": [
[
{
"node": "Set input fields",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Summarize Content",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"When clicking \u2018Test workflow\u2019": {
"main": [
[
{
"node": "Bright Data MCP Client List Tools",
"type": "main",
"index": 0
}
]
]
},
"MCP Client for Price Drop Data Extract": {
"main": [
[
{
"node": "Structure Data Extract Using LLM",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model for Summarize Content": {
"ai_languageModel": [
[
{
"node": "Summarize Content",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Google Gemini Chat Model for Sentiment Analysis": {
"ai_languageModel": [
[
{
"node": "Sentiment Analysis",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"MCP Client for Price Drop Data Extract Within a Loop": {
"main": [
[
{
"node": "Summarize Content",
"type": "main",
"index": 0
},
{
"node": "Sentiment Analysis",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googlePalmApigoogleSheetsOAuth2ApimcpClientApi
Pro
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About this workflow
Community nodes can only be installed on self-hosted instances of n8n.
Source: https://n8n.io/workflows/4611/ — original creator credit. Request a take-down →
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