Ben van Steenbergen This workflow corresponds to n8n.io template #15177 — we link there as the canonical source.
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": "3smw3ch1i7q3sJ2A",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "AI Agent Cost Calculator",
"tags": [],
"nodes": [
{
"id": "e3bc701e-9a6e-4fb9-849a-c35da44dcf28",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
3520,
1968
],
"parameters": {
"color": 4,
"width": 450,
"height": 716,
"content": "## AI Agent Cost Calculator\n\nScans your AI agent workflows every hour, extracts token usage per model, calculates the estimated USD cost, and stores a receipt in an n8n Data Table.\n\nSupports **Claude, OpenAI, Gemini, Perplexity** and any future model.\n\n## How to setup\n\n**Step 1**: Create a Data Table called `execution_receipts` with columns:\n`workflowid` (text) \u00b7 `executionid` (text) \u00b7 `receipt` (text) \u00b7 `created_at` (text) \u00b7 `units` (number)\n\n**Step 2**: Configure the 3 marked nodes:\n\n- **1.1** \u2192 Set your n8n API credential\n- **1.2** \u2192 Set your n8n API credential\n- **1.3** \u2192 Select your Data Table\n\n\n**Step 3**: Tag your AI agent workflows with `agent`\n\n\n**Step 4**: Activate the workflow\n\nTo add pricing for a new model, add one line to `MODEL_RATES` in the code node.\n\nSelf-hosted? Set `N8N_ENABLED_MODULES=data-table`."
},
"typeVersion": 1
},
{
"id": "0662b756-f02e-4a25-96c3-26830089e3b6",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
4048,
2240
],
"parameters": {
"color": 2,
"width": 630,
"height": 240,
"content": "## Collect Workflows\nFetches all workflows tagged `agent` and loops through them one by one."
},
"typeVersion": 1
},
{
"id": "909f1174-32f5-4935-b683-e63ed07393f5",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
4512,
2656
],
"parameters": {
"color": 6,
"width": 528,
"height": 196,
"content": "## Extract Token Usage\nPulls all executions per workflow, parses AI model token data, and calculates USD cost using the `MODEL_RATES` pricing table."
},
"typeVersion": 1
},
{
"id": "ff2f390d-9c9a-434a-a09e-26b4fac7d00c",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
4688,
2112
],
"parameters": {
"color": 3,
"width": 820,
"height": 218,
"content": "## Store Receipts\nFilters out empty results and saves each receipt to the `execution_receipts` Data Table."
},
"typeVersion": 1
},
{
"id": "7aef630f-a314-4baa-a833-d7d191f68587",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
5056,
2656
],
"parameters": {
"color": 5,
"width": 428,
"height": 198,
"content": "\ud83e\uddfe **itonomy.nl** \u00b7 Built by Ben van Steenbergen\n\n*This workflow costs less to run than the agents it monitors.*\n\nLike it? Let me know! [Follow me on LinkedIn](https://www.linkedin.com/in/ben-van-steenbergen-9006b37/)"
},
"typeVersion": 1
},
{
"id": "83a2f90e-0fb0-4b40-b730-22f982ec7d2f",
"name": "Hourly Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
4080,
2368
],
"parameters": {
"rule": {
"interval": [
{
"triggerAtMinute": 10
}
]
}
},
"typeVersion": 1.2
},
{
"id": "15036d2b-7209-422c-8d6a-a972f102567a",
"name": "1.1 Get AI Agent Workflows",
"type": "n8n-nodes-base.n8n",
"position": [
4256,
2368
],
"parameters": {
"filters": {
"tags": "agent",
"activeWorkflows": false,
"excludePinnedData": true
},
"requestOptions": {}
},
"typeVersion": 1
},
{
"id": "9c99328d-3866-436b-b351-423a9070626c",
"name": "Loop Workflows",
"type": "n8n-nodes-base.splitInBatches",
"position": [
4464,
2368
],
"parameters": {
"options": {
"reset": false
}
},
"typeVersion": 3
},
{
"id": "0e9749fc-c8f3-479b-99d7-e3d0ca8ed395",
"name": "1.2 Get Workflow Executions",
"type": "n8n-nodes-base.n8n",
"onError": "continueErrorOutput",
"position": [
4704,
2480
],
"parameters": {
"filters": {
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
}
},
"options": {
"activeWorkflows": true
},
"resource": "execution",
"returnAll": true,
"requestOptions": {}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "46b55b0e-fbc7-4870-92f4-36f5fad06cac",
"name": "Extract Token Usage & Cost",
"type": "n8n-nodes-base.code",
"position": [
4912,
2480
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "// AI Agent Cost Calculator \u2014 Token Usage & Cost Extractor\n// Supports: Anthropic Claude, OpenAI, Google Gemini, Perplexity\n// To add a new model, add an entry to MODEL_RATES below.\n\nif (Object.keys($json).length === 0) return {};\n\nconst usage = $json.data?.resultData?.runData;\nconst workflowId = $json.workflowId;\nconst runId = $json.id;\n\nif (!usage) return {};\n\n// \u2500\u2500 Model rates (USD per 1M tokens) \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n// Add new models here as providers release them.\n// Format: \"model-id\": { input: $/1M, output: $/1M }\nconst MODEL_RATES = {\n // \u2500\u2500 Anthropic Claude \u2500\u2500\n \"claude-opus-4-7\": { input: 5.00, output: 25.00 },\n \"claude-opus-4-6\": { input: 5.00, output: 25.00 },\n \"claude-sonnet-4-6\": { input: 3.00, output: 15.00 },\n \"claude-sonnet-4-5-20250929\": { input: 3.00, output: 15.00 },\n \"claude-sonnet-4-5\": { input: 3.00, output: 15.00 },\n \"claude-haiku-4-5-20251001\": { input: 1.00, output: 5.00 },\n \"claude-haiku-4-5\": { input: 1.00, output: 5.00 },\n \"claude-opus-4-5-20251101\": { input: 5.00, output: 25.00 },\n \"claude-opus-4-5\": { input: 5.00, output: 25.00 },\n \"claude-opus-4-1-20250805\": { input: 15.00, output: 75.00 },\n \"claude-opus-4-1\": { input: 15.00, output: 75.00 },\n \"claude-opus-4-20250514\": { input: 15.00, output: 75.00 },\n \"claude-opus-4-0\": { input: 15.00, output: 75.00 },\n \"claude-sonnet-4-20250514\": { input: 3.00, output: 15.00 },\n \"claude-sonnet-4-0\": { input: 3.00, output: 15.00 },\n \"claude-3-7-sonnet-20250219\": { input: 3.00, output: 15.00 },\n \"claude-3-5-sonnet-20241022\": { input: 3.00, output: 15.00 },\n \"claude-3-5-sonnet-20240620\": { input: 3.00, output: 15.00 },\n \"claude-3-5-haiku-20241022\": { input: 0.80, output: 4.00 },\n \"claude-3-opus-20240229\": { input: 15.00, output: 75.00 },\n \"claude-3-sonnet-20240229\": { input: 3.00, output: 15.00 },\n \"claude-3-haiku-20240307\": { input: 0.25, output: 1.25 },\n\n // \u2500\u2500 OpenAI \u2500\u2500\n \"gpt-4.1\": { input: 2.00, output: 8.00 },\n \"gpt-4.1-mini\": { input: 0.40, output: 1.60 },\n \"gpt-4.1-nano\": { input: 0.10, output: 0.40 },\n \"gpt-4o\": { input: 2.50, output: 10.00 },\n \"gpt-4o-mini\": { input: 0.15, output: 0.60 },\n \"gpt-4-turbo\": { input: 5.00, output: 15.00 },\n \"gpt-4\": { input: 30.00, output: 60.00 },\n \"gpt-3.5-turbo\": { input: 0.50, output: 1.50 },\n \"o4-mini\": { input: 1.10, output: 4.40 },\n \"o3\": { input: 2.00, output: 8.00 },\n \"o3-mini\": { input: 1.10, output: 4.40 },\n \"o3-pro\": { input: 20.00, output: 80.00 },\n \"o1\": { input: 15.00, output: 60.00 },\n \"o1-mini\": { input: 1.10, output: 4.40 },\n\n // \u2500\u2500 Google Gemini \u2500\u2500\n \"gemini-2.5-pro\": { input: 1.25, output: 10.00 },\n \"gemini-2.5-flash\": { input: 0.30, output: 2.50 },\n \"gemini-2.5-flash-lite\": { input: 0.10, output: 0.40 },\n \"gemini-2.0-flash\": { input: 0.15, output: 0.60 },\n \"gemini-2.0-flash-lite\": { input: 0.075, output: 0.30 },\n \"gemini-1.5-pro\": { input: 1.25, output: 5.00 },\n \"gemini-1.5-flash\": { input: 0.075, output: 0.30 },\n \"gemini-1.5-flash-8b\": { input: 0.0375,output: 0.15 },\n\n // \u2500\u2500 Perplexity \u2500\u2500\n \"sonar\": { input: 1.00, output: 1.00 },\n \"sonar-pro\": { input: 3.00, output: 15.00 },\n \"sonar-reasoning\": { input: 1.00, output: 5.00 },\n \"sonar-reasoning-pro\": { input: 2.00, output: 8.00 },\n};\n\nfunction calculateCost(model, promptTokens, completionTokens) {\n const rates = MODEL_RATES[model];\n if (!rates) return null;\n const inputCost = (promptTokens / 1000000) * rates.input;\n const outputCost = (completionTokens / 1000000) * rates.output;\n return Math.round((inputCost + outputCost) * 1000000) / 1000000;\n}\n\nconst receipt = {};\nreceipt[workflowId] = {};\nreceipt[workflowId][runId.toString()] = {};\n\nfor (const key in usage) {\n if (!Object.prototype.hasOwnProperty.call(usage, key)) continue;\n const steps = usage[key];\n\n for (const i in steps) {\n try {\n const element = steps[i];\n const elementData = element.data;\n const elementDataOverride = element.inputOverride;\n\n if (!elementData) continue;\n\n let model = undefined;\n let tokenData = undefined;\n\n // LLM nodes: Anthropic, OpenAI, Gemini (ai_languageModel output)\n if (Object.prototype.hasOwnProperty.call(elementData, 'ai_languageModel')) {\n const override = elementDataOverride?.['ai_languageModel']?.[0]?.[0]?.json;\n const output = elementData['ai_languageModel']?.[0]?.[0]?.json;\n\n model = override?.options?.model\n ?? override?.options?.model_name\n ?? override?.model\n ?? output?.model\n ?? undefined;\n\n tokenData = output?.tokenUsageEstimate ?? output?.tokenUsage ?? undefined;\n\n // HTTP/API nodes: Perplexity and other REST-based LLMs\n } else if (Object.prototype.hasOwnProperty.call(elementData, 'main')) {\n const output = elementData['main']?.[0]?.[0]?.json;\n model = output?.model ?? undefined;\n tokenData = output?.usage ?? undefined;\n }\n\n if (model && tokenData) {\n const pt = tokenData.promptTokens ?? tokenData.prompt_tokens ?? 0;\n const ct = tokenData.completionTokens ?? tokenData.completion_tokens ?? 0;\n const tt = tokenData.totalTokens ?? tokenData.total_tokens ?? (pt + ct);\n const cost = calculateCost(model, pt, ct);\n\n const existing = receipt[workflowId][runId.toString()][model];\n if (existing && typeof existing === 'object' && existing.promptTokens !== undefined) {\n // Aggregate tokens when same model appears multiple times in one execution\n existing.promptTokens += pt;\n existing.completionTokens += ct;\n existing.totalTokens += tt;\n if (cost !== null) existing.costUSD = (existing.costUSD ?? 0) + cost;\n } else {\n receipt[workflowId][runId.toString()][model] = {\n promptTokens: pt,\n completionTokens: ct,\n totalTokens: tt,\n ...(cost !== null ? { costUSD: cost } : {})\n };\n }\n receipt[workflowId][runId.toString()]['createdAt'] = $json.startedAt ?? \"\";\n }\n } catch (e) {\n // Skip steps that cannot be parsed\n continue;\n }\n }\n}\n\nif (Object.keys(receipt[workflowId][runId.toString()]).length === 0) return {};\n\nreturn receipt;\n"
},
"executeOnce": false,
"typeVersion": 2
},
{
"id": "2f64c928-1c3f-41ff-af5e-cae9d6324c44",
"name": "Loop Receipts",
"type": "n8n-nodes-base.splitInBatches",
"position": [
4736,
2224
],
"parameters": {
"options": {
"reset": false
}
},
"typeVersion": 3
},
{
"id": "1cef6528-b49a-4a1d-bfa5-f4fd98cbfae0",
"name": "Has Usage Data?",
"type": "n8n-nodes-base.if",
"position": [
4944,
2240
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "96b37396-1c38-423d-9d9e-32f1a99fa391",
"operator": {
"type": "number",
"operation": "gt"
},
"leftValue": "={{ $json.keys().length }}",
"rightValue": 0
}
]
}
},
"typeVersion": 2.2
},
{
"id": "79cd6d09-997e-416f-8f3a-951feec99f7d",
"name": "1.3 Save Receipt to Data Table",
"type": "n8n-nodes-base.dataTable",
"position": [
5280,
2224
],
"parameters": {
"columns": {
"value": {
"units": "1",
"receipt": "={{ $json[$json.keys().first()][$json[$json.keys().first()].keys().first()].toJsonString() }}",
"created_at": "={{ $json[$json.keys().first()][$json[$json.keys().first()].keys().first()]['createdAt'] ?? DateTime.now().format('yyyy-MM-dd HH:mm:ss') }}",
"workflowid": "={{ $json.keys().first() }}",
"executionid": "={{ $json[$json.keys().first()].keys().first() }}"
},
"schema": [
{
"id": "workflowid",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "workflowid",
"defaultMatch": false
},
{
"id": "executionid",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "executionid",
"defaultMatch": false
},
{
"id": "receipt",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "receipt",
"defaultMatch": false
},
{
"id": "created_at",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "created_at",
"defaultMatch": false
},
{
"id": "units",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "units",
"defaultMatch": false
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"dataTableId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultName": "execution_receipts"
}
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "6445f510-a0fa-49a9-9a02-b94dff0d016d",
"connections": {
"Loop Receipts": {
"main": [
[],
[
{
"node": "Has Usage Data?",
"type": "main",
"index": 0
}
]
]
},
"Hourly Trigger": {
"main": [
[
{
"node": "1.1 Get AI Agent Workflows",
"type": "main",
"index": 0
}
]
]
},
"Loop Workflows": {
"main": [
[
{
"node": "Loop Receipts",
"type": "main",
"index": 0
}
],
[
{
"node": "1.2 Get Workflow Executions",
"type": "main",
"index": 0
}
]
]
},
"Has Usage Data?": {
"main": [
[
{
"node": "1.3 Save Receipt to Data Table",
"type": "main",
"index": 0
}
],
[
{
"node": "Loop Receipts",
"type": "main",
"index": 0
}
]
]
},
"1.1 Get AI Agent Workflows": {
"main": [
[
{
"node": "Loop Workflows",
"type": "main",
"index": 0
}
]
]
},
"Extract Token Usage & Cost": {
"main": [
[
{
"node": "Loop Workflows",
"type": "main",
"index": 0
}
]
]
},
"1.2 Get Workflow Executions": {
"main": [
[
{
"node": "Extract Token Usage & Cost",
"type": "main",
"index": 0
}
]
]
},
"1.3 Save Receipt to Data Table": {
"main": [
[
{
"node": "Loop Receipts",
"type": "main",
"index": 0
}
]
]
}
}
}
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About this workflow
Ever wondered how much your AI Agent is costing you per run?
Source: https://n8n.io/workflows/15177/ — original creator credit. Request a take-down →
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