ankitkansaldev This workflow corresponds to n8n.io template #5431 — we link there as the canonical source.
This workflow follows the Agent → Form Trigger 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": "demo_workflow_id",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Comprehensive Reuters News Intelligence System With Brightdata & Telegram Alerts",
"tags": [],
"nodes": [
{
"id": "cab6b73a-d522-47b1-b0af-6732358a5798",
"name": "Anthropic Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
-660,
0
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-sonnet-4-20250514",
"cachedResultName": "Claude 4 Sonnet"
},
"options": {}
},
"credentials": {
"anthropicApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "2e9f25b0-5ffb-4d2e-a848-fc2b0958ade3",
"name": "HTTP Request",
"type": "n8n-nodes-base.httpRequestTool",
"position": [
-400,
20
],
"parameters": {
"url": "https://api.brightdata.com/datasets/v3/trigger",
"method": "POST",
"options": {},
"jsonBody": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('JSON', `This HTTP POST request sends the user's chat input (like \"Election\") to the BrightData Reuters News collector. The collector uses this input to create a new scraping snapshot based on the keyword. The request body includes a sessionId, action, and chatInput, and the response will return a snapshot_id which will be used in the next steps to fetch the scraped data. \n[\n {\n \"keyword\": \"Gas shocks\",\n \"sort\": \"newest\"\n }\n]`, 'json') }}",
"sendBody": true,
"sendQuery": true,
"sendHeaders": true,
"specifyBody": "json",
"queryParameters": {
"parameters": [
{
"name": "dataset_id",
"value": "gd_lyptx9h74wtlvpnfu"
},
{
"name": "include_errors",
"value": "true"
},
{
"name": "type",
"value": "discover_new"
},
{
"name": "discover_by",
"value": "keyword"
},
{
"name": "limit_per_input",
"value": "2"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer YOUR_TOKEN_HERE"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "c8190def-19a1-4d93-a3c5-1c0939404d6b",
"name": "Check Scraping Status",
"type": "n8n-nodes-base.httpRequestTool",
"position": [
-120,
60
],
"parameters": {
"url": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('URL', `use snapshot id to create http request url \nfor example:\nhttps://api.brightdata.com/datasets/v3/progress/your_snapshot_id`, 'string') }}",
"options": {},
"sendQuery": true,
"sendHeaders": true,
"queryParameters": {
"parameters": [
{
"name": "format",
"value": "json"
}
]
},
"toolDescription": "Makes an HTTP request to check the status of snapshot_id and returns the status like \"ready\" or \"running\". If the status received is \"running\", then make another HTTP request.",
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer YOUR_TOKEN_HERE"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "51df9a2a-677b-4e6c-a3c6-2b7a55f9f266",
"name": "Fetch Snapshot Data",
"type": "n8n-nodes-base.httpRequestTool",
"position": [
200,
80
],
"parameters": {
"url": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('URL', `make http request URL with snapshot_id \nfor example:\nhttps://api.brightdata.com/datasets/v3/snapshot/your_snapshot_id`, 'string') }}",
"options": {},
"sendQuery": true,
"sendHeaders": true,
"queryParameters": {
"parameters": [
{
"name": "format",
"value": "json"
}
]
},
"toolDescription": "Makes an HTTP request when snapshot_id is in ready status and returns the response data",
"headerParameters": {
"parameters": [
{
"name": "Authorization",
"value": "Bearer YOUR_TOKEN_HERE"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "13a0c262-7ff5-4e34-8e92-f27cbc1c7f9a",
"name": "On form submission",
"type": "n8n-nodes-base.formTrigger",
"position": [
-700,
-300
],
"parameters": {
"options": {},
"formTitle": "Reuters News Intelligence",
"formFields": {
"values": [
{
"fieldLabel": "Keywords",
"requiredField": true
},
{
"fieldType": "dropdown",
"fieldLabel": "News Type",
"fieldOptions": {
"values": [
{
"option": "newest"
},
{
"option": "oldest"
},
{
"option": "relevance"
}
]
},
"requiredField": true
}
]
}
},
"typeVersion": 2.2
},
{
"id": "89648837-569a-4bbe-85e8-f91a7b7bad48",
"name": "Telegram",
"type": "n8n-nodes-base.telegram",
"position": [
200,
-300
],
"parameters": {
"text": "={{ $json.article_url }}{{ $json.heading }}{{ $json.description }}{{ $json.content }}",
"chatId": "DEMO_CHAT_ID",
"additionalFields": {}
},
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "07b29eb4-7241-436d-a2cc-a966726a8890",
"name": "sleep tool",
"type": "@n8n/n8n-nodes-langchain.toolCode",
"position": [
440,
0
],
"parameters": {
"jsCode": "await new Promise(resolve => setTimeout(resolve, 60 * 1000));\n\nreturn \"1 minute wait done\";",
"description": "Call this tool before checking snapshot_id status."
},
"typeVersion": 1.2
},
{
"id": "499deea0-4b84-4a13-9012-f62027c5771a",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-780,
-380
],
"parameters": {
"color": 3,
"width": 280,
"height": 240,
"content": "Trigger node that starts the workflow when a form is submitted with \"Keywords\" and \"News Type\"."
},
"typeVersion": 1
},
{
"id": "3dea92a2-dbd0-42b1-92e4-4b9cc5bc37bc",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-760,
-100
],
"parameters": {
"color": 6,
"width": 260,
"height": 220,
"content": "Sends the input to Claude (Anthropic's LLM) for language-based processing or prompt handling."
},
"typeVersion": 1
},
{
"id": "589e68d2-5a78-41fc-957a-2952510cca4b",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-460,
-380
],
"parameters": {
"color": 4,
"width": 320,
"height": 240,
"content": "Uses LangChain's AI agent to orchestrate actions based on the input and other node outputs."
},
"typeVersion": 1
},
{
"id": "b6e0daec-5f83-4abd-8910-828f1d87218f",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-460,
-60
],
"parameters": {
"width": 220,
"height": 220,
"content": "Sends a request to BrightData to trigger a new Reuters news scraping snapshot by keyword."
},
"typeVersion": 1
},
{
"id": "3f7f75c2-6923-4bcf-8561-ba5797a0feaf",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-200,
0
],
"parameters": {
"color": 5,
"width": 280,
"height": 220,
"content": "Verifies if the BrightData snapshot has finished processing and is ready to be fetched."
},
"typeVersion": 1
},
{
"id": "26841dd7-e136-44bf-b0b3-6e7eee2499dc",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
120,
0
],
"parameters": {
"color": 3,
"height": 220,
"content": "Retrieves the actual data (articles) from BrightData once the snapshot is ready."
},
"typeVersion": 1
},
{
"id": "dbbf1a00-115b-4753-b4e7-6713185b0788",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
-120,
-380
],
"parameters": {
"color": 5,
"height": 240,
"content": "JavaScript code node to extract, clean, and structure only the required article fields."
},
"typeVersion": 1
},
{
"id": "552878fd-455d-4c8d-92ce-df00167b955f",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
140,
-380
],
"parameters": {
"height": 240,
"content": "Sends the final cleaned news article data to a specified Telegram chat."
},
"typeVersion": 1
},
{
"id": "835f1987-d44a-47aa-aed8-c90e95266b80",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
380,
-60
],
"parameters": {
"color": 4,
"height": 220,
"content": "Waits for 1 minute before checking again to ensure snapshot has time to complete."
},
"typeVersion": 1
},
{
"id": "a644da6d-31a1-4231-a57e-d859f4a03b2b",
"name": "MCP for Data Fetching through Anthropic",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-440,
-300
],
"parameters": {
"text": "=Scrape the latest Reuters news articles based on the keyword: \"{{ $json.Keywords }}\".\nNews Type:\"{{ $json['News Type'] }}\"\nFor each matching article, return the following details in the output JSON:\n\narticle_title: The title of the article\n\nheadline: The headline shown on Reuters site\n\ndescription: The short summary or meta description of the article\n\ncontent: The full article content/body text\n\narticle_url: The full URL to the article\n\nNote:- Make sure there is no duplication and that each field is clean and readable.",
"options": {},
"promptType": "define"
},
"typeVersion": 2
},
{
"id": "f2858466-d520-411f-aebf-44aee942be5b",
"name": "Data Formatting",
"type": "n8n-nodes-base.code",
"position": [
-60,
-300
],
"parameters": {
"jsCode": "// Step 1: Raw scraped response\nconst rawOutput = $json[\"output\"];\n\n// Step 2: Extract the JSON array part from within triple backticks ```json ... ```\nconst matches = rawOutput.match(/```json\\s+([\\s\\S]*?)\\s+```/);\n\nif (!matches || matches.length < 2) {\n throw new Error(\"Could not find JSON block in output\");\n}\n\nconst articles = JSON.parse(matches[1]);\n\n// Step 3: Map and clean only the required fields\nconst cleanedArticles = articles.map(article => ({\n heading: article.headline || article.article_title || \"\",\n article_url: article.article_url || \"\",\n description: article.description || \"\",\n content: article.content || \"\"\n}));\n\n// Step 4: Return cleaned articles as individual items\nreturn cleanedArticles.map(item => ({ json: item }));\n"
},
"typeVersion": 2,
"alwaysOutputData": false
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "demo_version_id",
"connections": {
"sleep tool": {
"ai_tool": [
[
{
"node": "MCP for Data Fetching through Anthropic",
"type": "ai_tool",
"index": 0
}
]
]
},
"HTTP Request": {
"ai_tool": [
[
{
"node": "MCP for Data Fetching through Anthropic",
"type": "ai_tool",
"index": 0
}
]
]
},
"Data Formatting": {
"main": [
[
{
"node": "Telegram",
"type": "main",
"index": 0
}
]
]
},
"On form submission": {
"main": [
[
{
"node": "MCP for Data Fetching through Anthropic",
"type": "main",
"index": 0
}
]
]
},
"Fetch Snapshot Data": {
"ai_tool": [
[
{
"node": "MCP for Data Fetching through Anthropic",
"type": "ai_tool",
"index": 0
}
]
]
},
"Anthropic Chat Model": {
"ai_languageModel": [
[
{
"node": "MCP for Data Fetching through Anthropic",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Check Scraping Status": {
"ai_tool": [
[
{
"node": "MCP for Data Fetching through Anthropic",
"type": "ai_tool",
"index": 0
}
]
]
},
"MCP for Data Fetching through Anthropic": {
"main": [
[
{
"node": "Data Formatting",
"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.
anthropicApitelegramApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
A powerful n8n automation workflow that scrapes the latest Reuters news articles using Bright Data's web scraping capabilities and delivers intelligent news summaries directly to your Telegram chat.
Source: https://n8n.io/workflows/5431/ — original creator credit. Request a take-down →
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