This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "Power BI Data Analyst Agent",
"settings": {
"executionOrder": "v1"
},
"nodes": [
{
"parameters": {
"content": "## Power BI Data Analyst Agent\n**What it does:** Natural-language analytics over a Power BI semantic model. Agent writes DAX, hits the REST `executeQueries` API, builds charts.\n\n### Required credentials\n- **Microsoft OAuth2 API** (Service Principal, client_credentials grant, scope: `https://analysis.windows.net/powerbi/api/.default`) \u2014 attach to `list_tables_and_measures`, `get_table_columns`, `refresh_dataset`, AND inside the DAX sub-workflow's `Run DAX via REST API` node.\n- **OpenRouter API** \u2014 attach to `OpenRouter Chat Model`.\n- **Postgres (writable)** \u2014 attach to `Postgres Chat Memory` (stores conversations in `n8n_chat_histories`).\n\n### Before activating\n1. Register an Azure AD app and grant Power BI tenant access \u2014 see `docs/AZURE_AD_SETUP.md`.\n2. Add the Service Principal as Member/Contributor on the Power BI workspace.\n3. Open the **Config** node and paste your `group_id` (workspace GUID) + `dataset_id` (dataset GUID).\n4. Re-bind `run_dax` and `create_chart` tools to the imported sub-workflows (IDs differ per instance).\n\n### Demo prompts\n- *What tables and measures does this model have?*\n- *Show me total sales by product category as a bar chart*\n- *Refresh the dataset*",
"height": 540,
"width": 680,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-680,
-580
],
"id": "sticky-pbi-readme",
"name": "README"
},
{
"parameters": {
"public": true,
"mode": "hostedChat",
"initialMessages": "Hi! I'm your Power BI data analyst.\nAsk me about your semantic model \u2014 I can explore tables/measures, run DAX, build charts, and refresh the dataset.",
"options": {
"title": "Power BI Data Analyst",
"subtitle": "Ask questions about your Power BI model \u2014 get answers and charts.",
"responseMode": "lastNode"
}
},
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.1,
"position": [
-680,
0
],
"id": "pbi-chat-trigger",
"name": "When chat message received"
},
{
"parameters": {
"assignments": {
"assignments": [
{
"id": "gid",
"name": "group_id",
"value": "REPLACE_WITH_YOUR_WORKSPACE_GUID",
"type": "string"
},
{
"id": "did",
"name": "dataset_id",
"value": "REPLACE_WITH_YOUR_DATASET_GUID",
"type": "string"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.set",
"typeVersion": 3.4,
"position": [
-460,
0
],
"id": "pbi-config",
"name": "Config"
},
{
"parameters": {
"promptType": "auto",
"options": {
"maxIterations": 12,
"systemMessage": "You are a senior data analyst working over a Power BI semantic model. Your query language is DAX, not SQL. Your job is to turn user questions into DAX, execute it, and return decision-ready insights with charts.\n\n## Available tools\n- `list_tables_and_measures()` \u2014 returns tables and measures defined in the model. Call once per conversation to discover what's available.\n- `get_table_columns(table_name)` \u2014 columns + data types for ONE table. Call before writing DAX against a table you haven't inspected.\n- `run_dax(query)` \u2014 executes a DAX query and returns up to 200 rows with a `truncated` flag. Column names are flattened (no `[Table].[Column]` brackets).\n- `create_chart(chart_type, title, labels, series, x_label?, y_label?)` \u2014 turn results into a PNG chart. See chart rules below.\n- `refresh_dataset()` \u2014 triggers a dataset refresh. Call ONLY when the user explicitly asks to refresh.\n- `think(thought)` \u2014 scratchpad for planning or post-error reasoning.\n\n## DAX primer (you write these)\nEvery query starts with `EVALUATE`. Examples:\n```\n// Simple table dump (always wrap in TOPN for safety):\nEVALUATE TOPN(100, Customers, Customers[CustomerId])\n\n// Grouped aggregation \u2014 preferred for most analytics:\nEVALUATE\nSUMMARIZECOLUMNS(\n Product[Category],\n \"Revenue\", [Total Sales], // use existing measures when available\n \"Orders\", COUNTROWS(Sales)\n)\nORDER BY [Revenue] DESC\n\n// Filtered aggregation via CALCULATE:\nEVALUATE\nROW(\n \"LastMonthRevenue\",\n CALCULATE([Total Sales], DATESINPERIOD('Date'[Date], MAX('Date'[Date]), -1, MONTH))\n)\n\n// Time series:\nEVALUATE\nSUMMARIZECOLUMNS(\n 'Date'[Year-Month],\n \"Revenue\", [Total Sales]\n)\nORDER BY 'Date'[Year-Month]\n```\n\n## Hard rules\n1. **Prefer existing measures.** If `list_tables_and_measures` shows a measure like `[Total Sales]`, USE IT \u2014 don't re-derive with `SUMX(Sales, Sales[Qty]*Sales[Price])`. The modeler defined it for a reason (currency conversion, filters, exclusions).\n2. **Always wrap exploratory queries in TOPN(500, \u2026)** unless you're computing a single aggregate.\n3. **Quote table and column names** with single quotes if they contain spaces: `'Sales Order'[Order Date]`.\n4. **Never invent table/column/measure names.** If discovery didn't show it, say so.\n5. **Refresh is a write op.** Only call `refresh_dataset` when the user explicitly asks ('refresh the data', 'update the model'). For ambiguous requests, confirm first.\n6. On DAX error: call `think` \u2192 diagnose (wrong column, bad function, missing single quotes) \u2192 retry ONCE. After 2 fails, ask the user.\n7. If `run_dax` returns `truncated: true`, tell the user and add more filters \u2014 don't work with partial data silently.\n\n## Chart policy \u2014 default to yes\nGenerate a chart in 80%+ of responses. Skip only when:\n- Result is a single scalar (one number).\n- User explicitly said no chart / table only.\n- Result is 1 row \u00d7 1 col.\n\n**Chart type rules:**\n- Time series (dates, months) \u2192 `line`\n- Category comparison (by category, country, segment) \u2192 `bar` (horizontalBar if >8 categories)\n- Share of total (\u22646 slices) \u2192 `doughnut` or `pie`\n- Two numeric dimensions \u2192 `scatter`\n- Mixed magnitudes (e.g. count + revenue) \u2192 DO NOT combine. Pick ONE metric or call `create_chart` twice.\n\n**Calling create_chart:** pass `chart_type`, `title`, `labels` (array of strings), `series` (array of `{name, values}`), optional `x_label`/`y_label`. The tool assembles the Chart.js spec \u2014 don't send nested JSON.\n\n## Output formatting \u2014 STRICT\nEvery response follows this structure:\n1. **Bold headline** \u2014 the key insight in one sentence with the headline number(s).\n2. **Chart** \u2014 `` on its own line.\n3. **Data table** \u2014 proper markdown pipe tables with `| ---: |` right-alignment for numerics. Never space-aligned. Max 15 rows.\n4. **DAX** \u2014 fenced ```DAX block with the exact query you ran.\n5. **Observations** \u2014 2-4 non-obvious bullets.\n\nNumber formatting: money as `$1,234`, percents as `12.3%`, dates as `2025-04` (months) or `2025-04-15` (days). Never pad with filler text."
}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.9,
"position": [
-220,
0
],
"id": "pbi-agent",
"name": "Power BI Analyst Agent"
},
{
"parameters": {
"model": "anthropic/claude-sonnet-4.6",
"options": {
"temperature": 0.2
}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenRouter",
"typeVersion": 1,
"position": [
-380,
240
],
"id": "pbi-openrouter",
"name": "OpenRouter Chat Model"
},
{
"parameters": {
"sessionIdType": "customKey",
"sessionKey": "={{ $('When chat message received').item.json.sessionId }}",
"contextWindowLength": 10,
"tableName": "n8n_chat_histories"
},
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.3,
"position": [
-220,
240
],
"id": "pbi-memory",
"name": "Postgres Chat Memory"
},
{
"parameters": {
"toolDescription": "Lists every table and measure in the Power BI semantic model. Returns kind (table/measure), name, and description. Call once per conversation to discover what exists. Takes no input.",
"method": "POST",
"url": "=https://api.powerbi.com/v1.0/myorg/groups/{{ $('Config').item.json.group_id }}/datasets/{{ $('Config').item.json.dataset_id }}/executeQueries",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "microsoftOAuth2Api",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"queries\": [{\n \"query\": \"EVALUATE UNION(SELECTCOLUMNS(INFO.TABLES(), \\\"kind\\\", \\\"table\\\", \\\"name\\\", [Name], \\\"description\\\", [Description]), SELECTCOLUMNS(INFO.MEASURES(), \\\"kind\\\", \\\"measure\\\", \\\"name\\\", [Name], \\\"description\\\", [Description]))\"\n }],\n \"serializerSettings\": { \"includeNulls\": true }\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequestTool",
"typeVersion": 4.2,
"position": [
-60,
240
],
"id": "pbi-tool-list",
"name": "list_tables_and_measures"
},
{
"parameters": {
"toolDescription": "Gets column names and data types for ONE table in the Power BI model. Call before writing DAX against a table you haven't inspected yet. Input: `table_name` (string, unquoted, e.g. 'Sales').",
"method": "POST",
"url": "=https://api.powerbi.com/v1.0/myorg/groups/{{ $('Config').item.json.group_id }}/datasets/{{ $('Config').item.json.dataset_id }}/executeQueries",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "microsoftOAuth2Api",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"queries\": [{\n \"query\": \"EVALUATE FILTER(SELECTCOLUMNS(INFO.COLUMNS(), \\\"Table\\\", [Table], \\\"Column\\\", [ExplicitName], \\\"DataType\\\", [ExplicitDataType], \\\"IsKey\\\", [IsKey], \\\"Description\\\", [Description]), [Table] = \\\"{{ $fromAI('table_name', 'Unquoted table name to inspect, e.g. Sales or Customer', 'string') }}\\\")\"\n }],\n \"serializerSettings\": { \"includeNulls\": true }\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequestTool",
"typeVersion": 4.2,
"position": [
100,
240
],
"id": "pbi-tool-cols",
"name": "get_table_columns"
},
{
"parameters": {
"name": "run_dax",
"description": "Runs a DAX query against the Power BI dataset. Returns up to 200 rows with a `truncated` flag. Always start with EVALUATE. Wrap table dumps in TOPN(500,...) unless you're aggregating.",
"workflowId": {
"__rl": true,
"value": "VMJrZzsStikwQuCg",
"mode": "id"
},
"workflowInputs": {
"mappingMode": "defineBelow",
"value": {
"group_id": "={{ $('Config').item.json.group_id }}",
"dataset_id": "={{ $('Config').item.json.dataset_id }}",
"query": "={{ $fromAI('query', 'A DAX query starting with EVALUATE. Example: EVALUATE SUMMARIZECOLUMNS(Product[Category], \"Revenue\", [Total Sales])', 'string') }}"
},
"matchingColumns": [],
"schema": [
{
"id": "group_id",
"displayName": "group_id",
"required": true,
"type": "string",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
},
{
"id": "dataset_id",
"displayName": "dataset_id",
"required": true,
"type": "string",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
},
{
"id": "query",
"displayName": "query",
"required": true,
"type": "string",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"typeVersion": 2.1,
"position": [
260,
240
],
"id": "pbi-tool-dax",
"name": "run_dax"
},
{
"parameters": {
"name": "create_chart",
"description": "Renders a chart and returns a public PNG URL. Inputs: chart_type (bar|line|pie|doughnut|horizontalBar), title, labels (array of strings), series (array of {name, values}), optional x_label, y_label. Do NOT build a Chart.js config \u2014 the tool handles assembly.",
"workflowId": {
"__rl": true,
"value": "CPLsOqLT7ksR7WAE",
"mode": "id"
},
"workflowInputs": {
"mappingMode": "defineBelow",
"value": {
"chart_type": "={{ $fromAI('chart_type', 'One of: bar, line, pie, doughnut, horizontalBar', 'string') }}",
"title": "={{ $fromAI('title', 'Chart title, e.g. \"Revenue by Product Category\"', 'string') }}",
"labels": "={{ $fromAI('labels', 'Array of string labels', 'json') }}",
"series": "={{ $fromAI('series', 'Array of series objects, each {name, values}', 'json') }}",
"x_label": "={{ $fromAI('x_label', 'X-axis title, optional', 'string') }}",
"y_label": "={{ $fromAI('y_label', 'Y-axis title, optional', 'string') }}"
},
"matchingColumns": [],
"schema": [
{
"id": "chart_type",
"displayName": "chart_type",
"required": true,
"type": "string",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
},
{
"id": "title",
"displayName": "title",
"required": true,
"type": "string",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
},
{
"id": "labels",
"displayName": "labels",
"required": true,
"type": "array",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
},
{
"id": "series",
"displayName": "series",
"required": true,
"type": "array",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
},
{
"id": "x_label",
"displayName": "x_label",
"required": false,
"type": "string",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
},
{
"id": "y_label",
"displayName": "y_label",
"required": false,
"type": "string",
"display": true,
"canBeUsedToMatch": true,
"defaultMatch": false
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"typeVersion": 2.1,
"position": [
420,
240
],
"id": "pbi-tool-chart",
"name": "create_chart"
},
{
"parameters": {
"toolDescription": "Triggers a refresh of the Power BI dataset. ONLY call on explicit user request ('refresh the data', 'update the model'). Takes no input. Returns 202 Accepted if the refresh was queued.",
"method": "POST",
"url": "=https://api.powerbi.com/v1.0/myorg/groups/{{ $('Config').item.json.group_id }}/datasets/{{ $('Config').item.json.dataset_id }}/refreshes",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "microsoftOAuth2Api",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "={\n \"notifyOption\": \"NoNotification\"\n}",
"options": {}
},
"type": "n8n-nodes-base.httpRequestTool",
"typeVersion": 4.2,
"position": [
580,
240
],
"id": "pbi-tool-refresh",
"name": "refresh_dataset"
},
{
"parameters": {
"name": "think",
"description": "Scratchpad. Write a brief plan or diagnose a DAX error before retrying. Input: `thought` (string). Use generously before complex queries and ALWAYS after a tool error.",
"language": "javaScript",
"jsCode": "const t = typeof query === 'string' ? query : (query && query.thought) ? query.thought : JSON.stringify(query);\nreturn `Thought recorded at ${new Date().toISOString()}: ${t}`;",
"specifyInputSchema": true,
"schemaType": "manual",
"inputSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"thought\": { \"type\": \"string\", \"description\": \"Plan or diagnosis.\" }\n },\n \"required\": [\"thought\"]\n}"
},
"type": "@n8n/n8n-nodes-langchain.toolCode",
"typeVersion": 1.3,
"position": [
740,
240
],
"id": "pbi-tool-think",
"name": "think"
}
],
"connections": {
"When chat message received": {
"main": [
[
{
"node": "Config",
"type": "main",
"index": 0
}
]
]
},
"Config": {
"main": [
[
{
"node": "Power BI Analyst Agent",
"type": "main",
"index": 0
}
]
]
},
"OpenRouter Chat Model": {
"ai_languageModel": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Postgres Chat Memory": {
"ai_memory": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"list_tables_and_measures": {
"ai_tool": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"get_table_columns": {
"ai_tool": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"run_dax": {
"ai_tool": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"create_chart": {
"ai_tool": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"refresh_dataset": {
"ai_tool": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"think": {
"ai_tool": [
[
{
"node": "Power BI Analyst Agent",
"type": "ai_tool",
"index": 0
}
]
]
}
}
}
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About this workflow
Power BI Data Analyst Agent. Uses stickyNote, chatTrigger, agent, lmChatOpenRouter. Chat trigger; 12 nodes.
Source: https://github.com/MinaSaad1/n8n-powerbi-data-analyst-agent/blob/main/workflows/01-pbi-main-agent.json — original creator credit. Request a take-down →
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