Joseph LePage This workflow corresponds to n8n.io template #2768 — we link there as the canonical source.
This workflow follows the Chainllm → Chat 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": "QqbYH25we4JDZrZD",
"name": "\ud83d\udd0d\ud83d\udee0\ufe0f Tavily Search & Extract - Template",
"tags": [],
"nodes": [
{
"id": "e029204b-2e05-4262-b464-7c1b3a995f91",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-780,
-940
],
"parameters": {
"color": 4,
"width": 520,
"height": 940,
"content": "## Tavily API Search Endpoint\n\n**Base URL**: `https://api.tavily.com/search`\n**Method**: POST\n\n### Required Parameters\n- `query`: The search query string\n- `api_key`: Your Tavily API key\n\n### Optional Parameters\n- `search_depth`: \"basic\" or \"advanced\" (default: \"basic\")\n- `topic`: \"general\" or \"news\" (default: \"general\") \n- `max_results`: Maximum number of results to return (default: 5)\n- `include_images`: Include query-related images (default: false)\n- `include_answer`: Include AI-generated answer (default: false)\n- `include_raw_content`: Include parsed HTML content (default: false)\n- `include_domains`: List of domains to include\n- `exclude_domains`: List of domains to exclude\n- `time_range`: Filter by time range (\"day\", \"week\", \"month\", \"year\")\n- `days`: Number of days back for news results (default: 3)\n\n### Example Request\n```json\n{\n \"api_key\": \"tvly-YOUR_API_KEY\",\n \"query\": \"Who is Leo Messi?\",\n \"search_depth\": \"basic\",\n \"include_answer\": false,\n \"include_images\": true,\n \"max_results\": 5\n}\n```\n"
},
"typeVersion": 1
},
{
"id": "6c47edec-6c6e-460d-b098-f9a26caa5f8e",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-220,
-940
],
"parameters": {
"color": 6,
"width": 640,
"height": 720,
"content": "## Tavily API Extract Endpoint \n\n**Base URL**: `https://api.tavily.com/extract`\n**Method**: POST\n\n### Required Parameters\n- `urls`: Single URL string or array of URLs\n- `api_key`: Your Tavily API key\n\n### Optional Parameters\n- `include_images`: Include extracted images (default: false)\n\n### Example Request\n```json\n{\n \"api_key\": \"tvly-YOUR_API_KEY\", \n \"urls\": [\n \"https://en.wikipedia.org/wiki/Artificial_intelligence\",\n \"https://en.wikipedia.org/wiki/Machine_learning\"\n ]\n}\n```"
},
"typeVersion": 1
},
{
"id": "cacae1d1-c9ec-4c2f-ba5d-f782257697cc",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1240,
-940
],
"parameters": {
"color": 3,
"width": 420,
"height": 540,
"content": "## Tavily API Documentation\n\nThe Tavily REST API provides seamless access to Tavily Search, a powerful search engine for LLM agents, and Tavily Extract, an advanced web scraping solution optimized for LLMs.\n\nhttps://docs.tavily.com/docs/rest-api/examples\n\nhttps://docs.tavily.com/docs/rest-api/api-reference#parameters\n\nThe Tavily API provides two main endpoints for search and data extraction.\n\nThe API returns JSON responses containing:\n\n- Search results with titles, URLs, and content\n- Extracted raw content from specified URLs\n- Response time metrics\n- Any error messages for failed requests\n\n\n**Note**: Error handling should check for failed results in the response before processing.\n"
},
"typeVersion": 1
},
{
"id": "16e977f4-e72d-474c-a04b-3f3ad51cc322",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1240,
-360
],
"parameters": {
"width": 420,
"height": 360,
"content": "## Tavily Use Cases\n\n\ud83d\udcdc Why Use Tavily API for Data Enrichment?\n\nhttps://docs.tavily.com/docs/use-cases/data-enrichment\n\n\ud83d\udca1 Why Use Tavily API for Company Research?\n\nhttps://docs.tavily.com/docs/use-cases/company-research\n\n\ud83d\udd0d GPT Researcher\n\nhttps://docs.tavily.com/docs/gpt-researcher/introduction"
},
"typeVersion": 1
},
{
"id": "7e4d0b3c-761d-42b9-bbbe-6ceb366fdc6f",
"name": "Tavily Search",
"type": "n8n-nodes-base.httpRequest",
"position": [
-580,
-180
],
"parameters": {
"url": "https://api.tavily.com/search",
"body": "={\n \"api_key\": \"tvly-YOUR_API_KEY\",\n \"query\": \"What is n8n?\",\n \"search_depth\": \"basic\",\n \"include_answer\": false,\n \"include_images\": true,\n \"include_image_descriptions\": true,\n \"include_raw_content\": false,\n \"max_results\": 5,\n \"include_domains\": [],\n \"exclude_domains\": []\n}",
"method": "POST",
"options": {},
"sendBody": true,
"contentType": "raw",
"rawContentType": "application/json"
},
"typeVersion": 4.2
},
{
"id": "47c0bfcf-a187-4b15-b208-2458c934d5f7",
"name": "Tavily Extract",
"type": "n8n-nodes-base.httpRequest",
"position": [
40,
-400
],
"parameters": {
"url": "https://api.tavily.com/extract",
"body": "={\n \"api_key\": \"tvly-YOUR_API_KEY\",\n \"urls\": [\n \"https://en.wikipedia.org/wiki/Artificial_intelligence\"\n ]\n}",
"method": "POST",
"options": {},
"sendBody": true,
"contentType": "raw",
"rawContentType": "application/json"
},
"typeVersion": 4.2
},
{
"id": "47791d39-087b-4104-aa0d-ef98deee945c",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1940,
-1020
],
"parameters": {
"color": 7,
"width": 660,
"height": 1020,
"content": "## Tavily API Overview\nhttps://docs.tavily.com/docs/welcome\n\nThe Tavily API provides a specialized search engine built specifically for AI agents and LLM applications, offering two main endpoints:\n\n## Search Endpoint\n\nThe search endpoint enables intelligent web searching with:\n\n**Key Features**\n- Query-based search with customizable depth (\"basic\" or \"advanced\")\n- Topic filtering for general or news content\n- Control over result quantity and content type\n- Domain inclusion/exclusion capabilities\n- Time range filtering and news date restrictions\n\n## Extract Endpoint\n\nThe extract endpoint focuses on content retrieval:\n\n**Key Features**\n- Single or batch URL processing\n- Raw content extraction\n- Optional image extraction\n- Structured response format\n\n## Implementation Benefits\n\n**For AI Integration**\n- Optimized for RAG (Retrieval Augmented Generation)\n- Single API call handles searching, scraping and filtering\n- Customizable response formats\n- Built-in content relevance scoring\n\n**Technical Advantages**\n- JSON response format\n- Error handling for failed requests\n- Response time metrics\n- Flexible content filtering options\n\n\nThis API is designed to simplify the integration of real-time web data into AI applications while ensuring high-quality, relevant results through intelligent processing and filtering."
},
"typeVersion": 1
},
{
"id": "76b291bc-8c34-44f1-b366-09c9f51089e2",
"name": "Get Top Result",
"type": "n8n-nodes-base.set",
"position": [
-700,
140
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "a73e848c-f7e7-4b3a-ae99-930c577b47be",
"name": "results",
"type": "object",
"value": "={{ $json.results.first() }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "4b098e57-eff2-4e70-9429-23b5c3d936c2",
"name": "Tavily Extract Top Search",
"type": "n8n-nodes-base.httpRequest",
"position": [
-480,
140
],
"parameters": {
"url": "https://api.tavily.com/extract",
"body": "={\n \"api_key\": \"{{ $('Tavily API Key').item.json.api_key }}\",\n \"urls\": [\n \"{{ $json.results.url }}\"\n ]\n}",
"method": "POST",
"options": {},
"sendBody": true,
"contentType": "raw",
"rawContentType": "application/json"
},
"typeVersion": 4.2
},
{
"id": "f593e164-1c9d-46e6-a619-39fe621c829f",
"name": "Filter > 90%",
"type": "n8n-nodes-base.set",
"position": [
-920,
140
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "8fd0cfc4-7adc-45f9-a278-d217e362ebfb",
"name": "results",
"type": "array",
"value": "={{ $json.results.filter(item => item.score > 0.80) }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "fadd100c-0335-42c2-9c3d-48e6d17eb2f9",
"name": "Tavily Search Topic",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1140,
140
],
"parameters": {
"url": "https://api.tavily.com/search",
"body": "={\n \"api_key\": \"{{ $json.api_key }}\",\n \"query\": \"{{ $('Provide search topic via Chat window').item.json.chatInput }}\",\n \"search_depth\": \"basic\",\n \"include_answer\": false,\n \"include_images\": true,\n \"include_image_descriptions\": true,\n \"include_raw_content\": false,\n \"max_results\": 5,\n \"include_domains\": [],\n \"exclude_domains\": []\n}",
"method": "POST",
"options": {},
"sendBody": true,
"contentType": "raw",
"rawContentType": "application/json"
},
"typeVersion": 4.2
},
{
"id": "1bc5a21f-0f96-4951-9c88-0bec00b9c586",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-240,
300
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.1
},
{
"id": "994bb3ee-598b-4d3f-bcfc-16c9cca36657",
"name": "Summarize Web Page Content",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
-260,
140
],
"parameters": {
"text": "=Summarize this web content and provide in Markdown format: {{ $json.results[0].raw_content }}",
"promptType": "define"
},
"typeVersion": 1.5
},
{
"id": "d5520da7-f6bc-470e-ab96-e04097041f08",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1680,
40
],
"parameters": {
"color": 5,
"width": 1800,
"height": 400,
"content": "## Tavily Search and Extract with AI Summarization Example"
},
"typeVersion": 1
},
{
"id": "9bd6c18e-aabf-4719-b9c4-ac91b36891a1",
"name": "Tavily API Key",
"type": "n8n-nodes-base.set",
"position": [
-1360,
140
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "035660a9-bb58-4ecb-bad3-7f4d017fa69f",
"name": "api_key",
"type": "string",
"value": "tvly-YOUR_API_KEY"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "41f36ad7-7a2b-4732-89ec-fe6500768631",
"name": "Provide search topic via Chat window",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-1580,
140
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "0213756a-35c4-46a8-9b79-2e8a81852177",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1420,
320
],
"parameters": {
"color": 7,
"height": 80,
"content": "### Tavily API Key\nhttps://app.tavily.com/home"
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "e1f22fbb-9663-405c-b7b1-7e8b2d54ad0f",
"connections": {
"Filter > 90%": {
"main": [
[
{
"node": "Get Top Result",
"type": "main",
"index": 0
}
]
]
},
"Get Top Result": {
"main": [
[
{
"node": "Tavily Extract Top Search",
"type": "main",
"index": 0
}
]
]
},
"Tavily API Key": {
"main": [
[
{
"node": "Tavily Search Topic",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Summarize Web Page Content",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Tavily Search Topic": {
"main": [
[
{
"node": "Filter > 90%",
"type": "main",
"index": 0
}
]
]
},
"Tavily Extract Top Search": {
"main": [
[
{
"node": "Summarize Web Page Content",
"type": "main",
"index": 0
}
]
]
},
"Provide search topic via Chat window": {
"main": [
[
{
"node": "Tavily API Key",
"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.
openAiApi
Pro
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About this workflow
🔍 This n8n workflow integrates Tavily's search and extract APIs with AI summarization capabilities to process web content efficiently. Get your Tavily API key from https://app.tavily.com/home Replace in the "Tavily API Key" node Connect your OpenAI credentials to the "OpenAI…
Source: https://n8n.io/workflows/2768/ — original creator credit. Request a take-down →
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