Back to Answer currency rate questions from Gmail and chat with Gemini and Frankfurter API
Card snapshot
n8n-workflow-20312.n8n.io
·
2026-10-07 10:27:39 UTC
·
c3f2fc207420dc769a7cf03c0dc926bbce7a0510e37045473078b4363cd57800
This is a frozen copy of the agent's agent-card.json as we observed it at the timestamp above. We capture a new snapshot every time the card's content hash changes. Useful for: forensic drift analysis, verifying downstream callers see the right version, reproducing routing decisions made historically.
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{
"url": "https://n8n.io/blog/supercharging-your-conference-registration-process-with-n8n/",
"icon": "\ud83c\udfab",
"label": "Supercharging your conference registration process with n8n"
},
{
"url": "https://n8n.io/blog/no-code-ecommerce-workflow-automations/",
"icon": "store",
"label": "6 e-commerce workflows to power up your Shopify s"
},
{
"url": "https://n8n.io/blog/how-to-get-started-with-crm-automation-and-no-code-workflow-ideas/",
"icon": "\ud83d\udc65",
"label": "How to get started with CRM automation (with 3 no-code workflow ideas"
},
{
"url": "https://n8n.io/blog/automate-google-apps-for-productivity/",
"icon": "\ud83d\udca1",
"label": "15 Google apps you can combine and automate to increase productivity"
},
{
"url": "https://n8n.io/blog/your-business-doesnt-need-you-to-operate/",
"icon": " \ud83d\udda5\ufe0f",
"label": "Hey founders! Your business doesn't need you to operate"
},
{
"url": "https://n8n.io/blog/using-automation-to-boost-productivity-in-the-workplace/",
"icon": "\ud83d\udcaa",
"label": "Using Automation to Boost Productivity in the Workplace"
}
],
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/trigger-nodes/n8n-nodes-base.gmailtrigger/"
}
],
"credentialDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/credentials/google/oauth-single-service/"
}
]
},
"categories": [
"Communication"
],
"nodeVersion": "1.0",
"codexVersion": "1.0"
}
},
"group": "[\"trigger\"]",
"defaults": {
"name": "Gmail Trigger"
},
"iconData": {
"type": "file",
"fileBuffer": "data:image/svg+xml;base64,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"
},
"displayName": "Gmail Trigger",
"typeVersion": 1,
"nodeCategories": [
{
"id": 6,
"name": "Communication"
}
]
},
{
"id": 834,
"icon": "file:code.svg",
"name": "n8n-nodes-base.code",
"codex": {
"data": {
"alias": [
"cpde",
"Javascript",
"JS",
"Python",
"Script",
"Custom Code",
"Function"
],
"details": "The Code node allows you to execute JavaScript in your workflow.",
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.code/"
}
]
},
"categories": [
"Development",
"Core Nodes"
],
"nodeVersion": "1.0",
"codexVersion": "1.0",
"subcategories": {
"Core Nodes": [
"Helpers",
"Data Transformation"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "Code"
},
"iconData": {
"type": "file",
"fileBuffer": "data:image/svg+xml;base64,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"
},
"displayName": "Code",
"typeVersion": 2,
"nodeCategories": [
{
"id": 5,
"name": "Development"
},
{
"id": 9,
"name": "Core Nodes"
}
]
},
{
"id": 1119,
"icon": "fa:robot",
"name": "@n8n/n8n-nodes-langchain.agent",
"codex": {
"data": {
"alias": [
"LangChain",
"Chat",
"Conversational",
"Plan and Execute",
"ReAct",
"Tools"
],
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/"
}
]
},
"categories": [
"AI",
"Langchain"
],
"subcategories": {
"AI": [
"Agents",
"Root Nodes"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "AI Agent",
"color": "#404040"
},
"iconData": {
"icon": "robot",
"type": "icon"
},
"displayName": "AI Agent",
"typeVersion": 3,
"nodeCategories": [
{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1163,
"icon": "fa:database",
"name": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"codex": {
"data": {
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.memorybufferwindow/"
}
]
},
"categories": [
"AI",
"Langchain"
],
"subcategories": {
"AI": [
"Memory"
],
"Memory": [
"For beginners"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "Simple Memory"
},
"iconData": {
"icon": "database",
"type": "icon"
},
"displayName": "Simple Memory",
"typeVersion": 1,
"nodeCategories": [
{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1247,
"icon": "fa:comments",
"name": "@n8n/n8n-nodes-langchain.chatTrigger",
"codex": {
"data": {
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.chattrigger/"
}
]
},
"categories": [
"Core Nodes",
"Langchain"
]
}
},
"group": "[\"trigger\"]",
"defaults": {
"name": "When chat message received"
},
"iconData": {
"icon": "comments",
"type": "icon"
},
"displayName": "Chat Trigger",
"typeVersion": 1,
"nodeCategories": [
{
"id": 9,
"name": "Core Nodes"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1262,
"icon": "file:google.svg",
"name": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"codex": {
"data": {
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatgooglegemini/"
}
]
},
"categories": [
"AI",
"Langchain"
],
"subcategories": {
"AI": [
"Language Models",
"Root Nodes"
],
"Language Models": [
"Chat Models (Recommended)"
]
}
}
},
"group": "[\"transform\"]",
"defaults": {
"name": "Google Gemini Chat Model"
},
"iconData": {
"type": "file",
"fileBuffer": "data:image/svg+xml;base64,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"
},
"displayName": "Google Gemini Chat Model",
"typeVersion": 1,
"nodeCategories": [
{
"id": 25,
"name": "AI"
},
{
"id": 26,
"name": "Langchain"
}
]
},
{
"id": 1313,
"icon": "fa:comments",
"name": "@n8n/n8n-nodes-langchain.chat",
"codex": {
"data": {
"alias": [
"human",
"wait",
"hitl",
"respond",
"approve",
"confirm",
"send",
"message"
],
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.respondtochat/"
}
]
},
"categories": [
"Core Nodes",
"HITL",
"Langchain"
],
"subcategories": {
"HITL": [
"Human in the Loop"
]
}
}
},
"group": "[\"input\"]",
"defaults": {
"name": "Chat"
},
"iconData": {
"icon": "comments",
"type": "icon"
},
"displayName": "Chat",
"typeVersion": 1,
"nodeCategories": [
{
"id": 9,
"name": "Core Nodes"
},
{
"id": 26,
"name": "Langchain"
},
{
"id": 28,
"name": "HITL"
}
]
},
{
"id": 1315,
"icon": "fa:table",
"name": "n8n-nodes-base.dataTable",
"codex": {
"data": {
"alias": [
"data",
"table",
"knowledge",
"data table",
"table",
"sheet",
"database",
"data base",
"mysql",
"postgres",
"postgresql",
"airtable",
"supabase",
"noco",
"notion"
],
"details": "Data table",
"resources": {
"primaryDocumentation": [
{
"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.datatable/"
}
]
},
"categories": [
"Core Nodes",
"Development"
],
"nodeVersion": "1.0",
"codexVersion": "1.0",
"subcategories": {
"Core Nodes": [
"Helpers"
]
}
}
},
"group": "[\"input\",\"transform\"]",
"defaults": {
"name": "Data table"
},
"iconData": {
"icon": "table",
"type": "icon"
},
"displayName": "Data table",
"typeVersion": 1,
"nodeCategories": [
{
"id": 5,
"name": "Development"
},
{
"id": 9,
"name": "Core Nodes"
}
]
}
]
},
"detail": {
"description": "Quick Overview This workflow answers exchange-rate questions coming from Gmail or an n8n chat trigger using a Google Gemini AI agent that calls the Frankfurter exchange-rate API, caches successful rate responses in n8n Data Tables to avoid repeated model calls, logs usage metrics, and replies back on the originating channel. How it works 1. Triggers when a new Gmail message matching the exchange-rate search filter arrives or when an n8n chat message is received. 2. Normalizes incoming email and chat messages into a common format (session ID, user text, source channel, sender email) and processes them one at a time. 3. Extracts two ISO 4217 currency codes from the message to build a per-day cache key and looks up a previously saved response in an n8n Data Table. 4. If a fresh cached response exists (within the configured TTL), uses it directly without calling the AI model. 5. If there is no fresh cache hit, runs a Google Gemini-powered AI agent that calls the Frankfurter API to fetch the latest reference exchange rate and generates a one- or two-sentence plain-text reply. 6. Stores valid rate answers back into the cache, logs the query details (source, pair, cache hit, latency) to a second Data Table, and replies via n8n chat or Gmail depending on where the question originated. Setup 1. Add credentials for Gmail OAuth2 (for the Gmail trigger and email replies) and a Google Gemini (PaLM) API credential for the chat model. 2. Create or select two n8n Data Tables: one for the rate cache with columns cachekey (string), pair (string), response (string), cachedat (number) and one for the query log with columns loggedat (string), source (string), pair (string), cachehit (boolean), latencyms (number). 3. Update the Data Table selections in the cache lookup/save nodes and the log node, then review the Config values (cache TTL, email subject, fallback message) and adjust the Gmail search filter to match the senders and subjects you want to handle."
}
}