This workflow follows the Agent → 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 →
{
"name": "MCP Client - SeqBot",
"nodes": [
{
"parameters": {
"public": true,
"initialMessages": "Hi there! \ud83d\udc4b\nMy name is SeqBot. How can I assist you today?",
"options": {
"title": "SeqBot"
}
},
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.3,
"position": [
-720,
-64
],
"id": "eae485b3-b38f-49b3-9a87-77f163c85c92",
"name": "When chat message received"
},
{
"parameters": {
"endpointUrl": "https://tecval.app.n8n.cloud/mcp/e7770090-9193-49e3-a613-f13b1874b952",
"options": {
"timeout": 120000
}
},
"type": "@n8n/n8n-nodes-langchain.mcpClientTool",
"typeVersion": 1.1,
"position": [
-256,
192
],
"id": "20332ce9-c630-417e-a1b9-e03234792a22",
"name": "MCP Client"
},
{
"parameters": {
"promptType": "define",
"text": "={{$json.chatInput}}",
"options": {
"systemMessage": "Eres un agente que se conecta al MCP Server Trigger, y a las herramientas que tiene disponible.\n\nResponde siempre seg\u00fan la base de datos, nunca respondas informaci\u00f3n que no funciona\nDebes responder en ingles.\n\n{{ $json.chatInput }}"
}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 2.2,
"position": [
-512,
-64
],
"id": "1cfc5db4-f414-43a2-b833-34ff8b78a75d",
"name": "AI Agent"
},
{
"parameters": {
"model": {
"__rl": true,
"value": "gpt-4.1-mini",
"mode": "list",
"cachedResultName": "gpt-4.1-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
-640,
192
],
"id": "a917fbf8-781f-48b8-a4d6-8c3cf62d1048",
"name": "OpenAI Chat Model",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"contextWindowLength": 10
},
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
-448,
192
],
"id": "d41f6015-599e-4278-a4cd-03a15e1b8b4c",
"name": "Simple Memory"
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "f6f646d1-c36a-489e-b808-79b0bd542b94",
"leftValue": "={{ $json.message.content.inicio }}",
"rightValue": "",
"operator": {
"type": "number",
"operation": "exists",
"singleValue": true
}
},
{
"id": "aa35c305-0002-47d3-b06c-f52599515ae3",
"leftValue": "={{ $json.message.content.final }}",
"rightValue": "",
"operator": {
"type": "number",
"operation": "exists",
"singleValue": true
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
160,
-64
],
"id": "0cc0c1aa-d5b4-40a4-b97c-356f8787d2a1",
"name": "Is it about a biomarker region?"
},
{
"parameters": {
"url": "=https://api.genome.ucsc.edu/getData/sequence?genome=hg38;chrom={{ $('Analyze the agent response').item.json.message.content.cromosoma }};start={{ $('Analyze the agent response').item.json.message.content.inicio }};end={{ $('Analyze the agent response').item.json.message.content.final }}",
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
416,
-160
],
"id": "df3ca3a7-c25b-4a8c-b814-d95ae35e8d06",
"name": "UCSC Genome API"
},
{
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "let respuesta = $('AI Agent').item.json.output;\n\nconst cantidad = ($json.dna.toUpperCase().match(new RegExp('GCGC', \"g\")) || []).length;\n\nconst index = respuesta.indexOf('\u00bf');\nif(index > 0){\n respuesta = respuesta.substring(0, index) + '\\n- Sitios GCGC: ' + cantidad + '\\n- Secuencia: ' + $json.dna.toUpperCase() + '\\n\\n' + respuesta.substring(index);\n} else {\n respuesta = respuesta + '\\n- Sitios GCGC: ' + cantidad + '\\n- Secuencia: ' + $json.dna.toUpperCase() + '\\n\\n' + respuesta.substring(index);\n}\n\nreturn {\n output: respuesta\n}\n\n\n"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
720,
-160
],
"id": "6547b3e0-efc0-4ee2-9ef3-bd96979bebdb",
"name": "Attach the sequence"
},
{
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "\nreturn {output:$('AI Agent').item.json.output};"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
416,
64
],
"id": "277d9c4b-e406-480d-a267-c8c79b5748fc",
"name": "Build a response"
},
{
"parameters": {
"modelId": {
"__rl": true,
"value": "chatgpt-4o-latest",
"mode": "list",
"cachedResultName": "CHATGPT-4O-LATEST"
},
"messages": {
"values": [
{
"content": "=Analiza el siguiente texto y si meciona region de biomarcadores para un gen especifico extrae del mismo la siguiente informacion Inicio, Fin y Chromosoma y retorna esa respuesta en formato JSON con esta estructura: \n\n{ inicio: <posicion inicial> \n final: <posicion final>\n cromosoma: <n\u00famero de cromosoma> \n}\n{{ $json.output }}"
}
]
},
"jsonOutput": true,
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.openAi",
"typeVersion": 1.8,
"position": [
-192,
-64
],
"id": "154fb4c4-2114-40dd-afa6-ba645989196d",
"name": "Analyze the agent response",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
}
],
"connections": {
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"MCP Client": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"AI Agent": {
"main": [
[
{
"node": "Analyze the agent response",
"type": "main",
"index": 0
}
]
]
},
"Is it about a biomarker region?": {
"main": [
[
{
"node": "UCSC Genome API",
"type": "main",
"index": 0
}
],
[
{
"node": "Build a response",
"type": "main",
"index": 0
}
]
]
},
"UCSC Genome API": {
"main": [
[
{
"node": "Attach the sequence",
"type": "main",
"index": 0
}
]
]
},
"Analyze the agent response": {
"main": [
[
{
"node": "Is it about a biomarker region?",
"type": "main",
"index": 0
}
]
]
}
},
"active": true,
"settings": {
"executionOrder": "v1"
},
"versionId": "9f4e8f5b-217e-46cc-8e5b-cbbd8fab1449",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "JPS5Xs2fFYTgwds1",
"tags": []
}
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
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How this works
This workflow enables biologists and researchers to swiftly analyse genomic sequences by querying biomarkers through a simple chat interface, delivering precise results without manual data hunting. It suits teams handling DNA or RNA data who need quick insights into specific regions, integrating seamlessly with OpenAI for intelligent processing and the UCSC Genome API for reliable sequence retrieval. The core step involves an AI agent that interprets your query, checks for biomarker relevance, fetches the genomic data, and attaches the exact sequence for immediate use.
Use this workflow when exploring biomarker-related genomic queries in real-time chats, such as validating a gene region's sequence during a lab discussion. Avoid it for high-volume batch processing or non-genomic topics, where simpler tools suffice. Common variations include swapping OpenAI for another LLM or adding email notifications for sequence outputs.
About this workflow
MCP Client - SeqBot. Uses chatTrigger, mcpClientTool, agent, lmChatOpenAi. Chat trigger; 10 nodes.
Source: https://gitlab.com/cancer-tools/ia-mcp-seqbot-client/-/blob/main/MCP_Client_-_SeqBot.json — original creator credit. Request a take-down →
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