Grace Gbadamosi This workflow corresponds to n8n.io template #6598 — we link there as the canonical source.
This workflow follows the Agent → Error 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": "Si4R0nr5H78eQWI8",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Multi-CRM data sync to Google Sheets with AI deduplication",
"tags": [],
"nodes": [
{
"id": "9ebee5e9-64a0-44d3-b2f7-e80a4288bede",
"name": "Daily Sync Schedule",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-1088,
-160
],
"parameters": {
"rule": {
"interval": [
{
"field": "cronExpression",
"expression": "0 2 * * *"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "120c27c5-c98e-4cc7-ac5d-e816d6b8b7a9",
"name": "Manual Sync Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
-1088,
-16
],
"parameters": {
"path": "crm-sync-manual",
"options": {},
"httpMethod": "POST",
"responseMode": "lastNode"
},
"typeVersion": 2
},
{
"id": "fbf40d96-d15a-4de2-b14c-10dc01758ef8",
"name": "Trigger Router",
"type": "n8n-nodes-base.merge",
"position": [
-880,
-96
],
"parameters": {
"mode": "chooseBranch",
"output": "input1"
},
"typeVersion": 3.2
},
{
"id": "7b87c097-0337-4dc5-b33c-35b0ceebc906",
"name": "Configuration Center",
"type": "n8n-nodes-base.set",
"position": [
-688,
-96
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "89af6d5e-7c8b-4f3e-a9d2-1b5e4c8f9a7d",
"name": "runId",
"type": "string",
"value": "={{ $now.toFormat('yyyy-MM-dd-HHmmss') }}"
},
{
"id": "a7c5e3b2-9d4f-4e8a-b6c1-8f3e5d7a9b2c",
"name": "stagingSheetId",
"type": "string",
"value": "YOUR_STAGING_SHEET_ID"
},
{
"id": "c3e7f9a5-2b1d-4c8e-a7f6-9e5d3b1c7a8f",
"name": "masterSheetId",
"type": "string",
"value": "YOUR_MASTER_SHEET_ID"
},
{
"id": "d9b3c7e2-8f5a-4e1d-9c7b-3a5e8d2f9c1b",
"name": "hubspotApiKey",
"type": "string",
"value": "YOUR_HUBSPOT_API_KEY"
},
{
"id": "e5f8a3c7-1b9d-4c2e-8a7f-5b3e9d1c8f7a",
"name": "pipedriveApiKey",
"type": "string",
"value": "YOUR_PIPEDRIVE_API_KEY"
},
{
"id": "f2c8e7a9-5d3b-4e1c-9a8f-7b5e3d2c9f1a",
"name": "salesforceInstance",
"type": "string",
"value": "YOUR_SALESFORCE_INSTANCE"
},
{
"id": "a8e5f3c7-9b1d-4e2a-8c7f-5a3e9b1d7c8f",
"name": "salesforceAccessToken",
"type": "string",
"value": "YOUR_SALESFORCE_ACCESS_TOKEN"
},
{
"id": "b7d9c3e5-8f2a-4c1e-9b7a-3e5f8d2a9c1b",
"name": "batchSize",
"type": "number",
"value": 100
},
{
"id": "c5e8f7a3-1b9d-4c2e-8a7f-9b3e5d1c8f7a",
"name": "qualityThreshold",
"type": "number",
"value": 0.7
},
{
"id": "d7b9e5c3-8f2a-4c1e-9a7f-2b3e5d1c8f7a",
"name": "deduplicationKeys",
"type": "json",
"value": "[\"email\", \"companyName\", \"phone\"]"
},
{
"id": "e9c7b5a3-1f8d-4c2e-8a7f-5b3e9d1c8f7a",
"name": "requiredFields",
"type": "json",
"value": "[\"email\", \"firstName\", \"lastName\", \"companyName\"]"
},
{
"id": "f5a8c7e3-9b1d-4e2a-8c7f-3b5e9d1c8f7a",
"name": "slackWebhookUrl",
"type": "string",
"value": "YOUR_SLACK_WEBHOOK_URL"
},
{
"id": "a3b7c9e5-8f2a-4c1e-9a7f-1b5e3d2c9f1a",
"name": "mcpServerEndpoint",
"type": "string",
"value": "http://localhost:8000"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "edf6a60a-0853-4406-a261-0d2af0e2bd65",
"name": "Parallel CRM Fetcher",
"type": "n8n-nodes-base.code",
"position": [
-480,
-96
],
"parameters": {
"jsCode": "// Combine all results\nconst allData = [...hubspotData, ...pipedriveData, ...salesforceData];\n\n// Export data for pandas processing\nconst csvData = allData.map(record => ({\n source: record.source,\n recordId: record.recordId,\n firstName: record.firstName,\n lastName: record.lastName,\n email: record.email,\n companyName: record.companyName,\n phone: record.phone,\n stage: record.stage,\n lastModified: record.lastModified\n}));\n\n// Create CSV content manually (Papa Parse not needed)\nconst csvHeaders = ['source','recordId','firstName','lastName','email','companyName','phone','stage','lastModified'];\nconst csvRows = csvData.map(record => \n csvHeaders.map(header => `\"${record[header] || ''}\"`).join(',')\n);\nconst csvContent = [csvHeaders.join(','), ...csvRows].join('\\n');\n\n// Add metadata and return\nconst output = {\n runId: config.runId,\n timestamp: new Date().toISOString(),\n totalRecords: allData.length,\n breakdown: {\n hubspot: hubspotData.length,\n pipedrive: pipedriveData.length,\n salesforce: salesforceData.length\n },\n errors: errors,\n data: allData,\n csvData: csvContent,\n csvFilePath: `/tmp/crm_data_${config.runId}.csv`\n};\n\nreturn output;"
},
"typeVersion": 2
},
{
"id": "c8b8fd39-59f4-4a98-9a96-310887f8c46d",
"name": "Master Database Writer",
"type": "n8n-nodes-base.googleSheets",
"position": [
144,
-320
],
"parameters": {
"columns": {
"value": {},
"schema": [
{
"id": "email",
"type": "string",
"display": true,
"required": false,
"displayName": "email",
"defaultMatch": true,
"canBeUsedToMatch": true
}
],
"mappingMode": "autoMapInputData",
"matchingColumns": [
"email"
]
},
"options": {
"cellFormat": "USER_ENTERED"
},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Master_CRM_Data"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Configuration Center').item.json.masterSheetId }}"
},
"authentication": "serviceAccount"
},
"credentials": {
"googleApi": {
"name": "<your credential>"
}
},
"typeVersion": 4.4
},
{
"id": "b5e1acea-e75d-43ec-aae9-838923e124e1",
"name": "Quality Report Generator",
"type": "n8n-nodes-base.code",
"position": [
368,
-96
],
"parameters": {
"jsCode": "// Quality Report Generator and Notifier\nconst config = $('Configuration Center').first().json;\nconst crmData = $('Parallel CRM Fetcher').first().json;\nconst processedData = $input.all();\n\n// Calculate statistics\nconst stats = {\n runId: config.runId,\n timestamp: new Date().toISOString(),\n duration: Math.round((new Date() - new Date(crmData.timestamp)) / 1000),\n \n // Record counts\n totalFetched: crmData.totalRecords,\n totalProcessed: processedData.length,\n recordsWritten: processedData.filter(r => !r.json.isDuplicate).length,\n duplicatesFound: processedData.filter(r => r.json.isDuplicate).length,\n \n // Quality metrics\n averageQuality: (processedData.reduce((sum, r) => sum + (r.json.dataQualityScore || 0), 0) / processedData.length).toFixed(3),\n highQuality: processedData.filter(r => r.json.dataQualityScore >= config.qualityThreshold).length,\n lowQuality: processedData.filter(r => r.json.dataQualityScore < config.qualityThreshold).length,\n \n // Source breakdown\n breakdown: crmData.breakdown,\n \n // Issues summary\n topIssues: {},\n errors: crmData.errors\n};\n\n// Analyze quality issues\nprocessedData.forEach(record => {\n if (record.json.qualityIssues) {\n record.json.qualityIssues.forEach(issue => {\n stats.topIssues[issue] = (stats.topIssues[issue] || 0) + 1;\n });\n }\n});\n\n// Sort issues by frequency\nstats.topIssues = Object.entries(stats.topIssues)\n .sort((a, b) => b[1] - a[1])\n .slice(0, 5)\n .reduce((obj, [key, value]) => ({ ...obj, [key]: value }), {});\n\n// Create Slack notification\nconst slackMessage = {\n blocks: [\n {\n type: \"header\",\n text: {\n type: \"plain_text\",\n text: \"\ud83d\udd04 CRM Sync Completed\"\n }\n },\n {\n type: \"section\",\n fields: [\n { type: \"mrkdwn\", text: `*Run ID:* ${stats.runId}` },\n { type: \"mrkdwn\", text: `*Duration:* ${stats.duration}s` },\n { type: \"mrkdwn\", text: `*Records Processed:* ${stats.totalProcessed}` },\n { type: \"mrkdwn\", text: `*Duplicates Found:* ${stats.duplicatesFound}` },\n { type: \"mrkdwn\", text: `*Average Quality:* ${stats.averageQuality}` },\n { type: \"mrkdwn\", text: `*High Quality:* ${stats.highQuality}` }\n ]\n }\n ]\n};\n\n// Add error section if any\nif (stats.errors.length > 0) {\n slackMessage.blocks.push({\n type: \"section\",\n text: {\n type: \"mrkdwn\",\n text: `\u26a0\ufe0f *Errors:* ${stats.errors.map(e => `${e.source}: ${e.error}`).join(', ')}`\n }\n });\n}\n\n// Send to Slack\nif (config.slackWebhookUrl) {\n await $http.post(config.slackWebhookUrl, {\n body: slackMessage,\n headers: { 'Content-Type': 'application/json' }\n });\n}\n\n// Write report to Google Sheets\nconst reportData = {\n ...stats,\n topIssues: JSON.stringify(stats.topIssues),\n errors: JSON.stringify(stats.errors)\n};\n\n// Return report for sheet writing\nreturn reportData;"
},
"typeVersion": 2
},
{
"id": "6cc65daf-89df-4142-a8d1-3b73c981d7b8",
"name": "Report Writer",
"type": "n8n-nodes-base.googleSheets",
"position": [
768,
-96
],
"parameters": {
"columns": {
"value": {},
"mappingMode": "autoMapInputData"
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Quality_Reports"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Configuration Center').item.json.masterSheetId }}"
},
"authentication": "serviceAccount"
},
"credentials": {
"googleApi": {
"name": "<your credential>"
}
},
"typeVersion": 4.4
},
{
"id": "e936e062-489d-44d4-93d0-7b6f0b15790a",
"name": "Error Handler",
"type": "n8n-nodes-base.errorTrigger",
"position": [
-1088,
288
],
"parameters": {},
"typeVersion": 1
},
{
"id": "ddb1762a-799c-4552-948e-817d5014ae8a",
"name": "Error Processor",
"type": "n8n-nodes-base.code",
"position": [
-816,
288
],
"parameters": {
"jsCode": "// Comprehensive Error Handler\nconst error = $input.first().json;\nconst config = $('Configuration Center').first()?.json || {};\n\n// Create detailed error log\nconst errorLog = {\n timestamp: new Date().toISOString(),\n runId: config.runId || 'unknown',\n errorType: error.name || 'UnknownError',\n errorMessage: error.message || 'No error message',\n errorStack: error.stack || '',\n nodeName: error.node?.name || 'Unknown node',\n nodeType: error.node?.type || 'Unknown type',\n workflowId: $execution.workflowId,\n executionId: $execution.id,\n context: JSON.stringify(error)\n};\n\n// Log to console for debugging\nconsole.error('Workflow Error:', errorLog);\n\n// Send error notification to Slack if configured\nif (config.slackWebhookUrl) {\n const slackError = {\n blocks: [\n {\n type: \"header\",\n text: {\n type: \"plain_text\",\n text: \"\u274c CRM Sync Error\"\n }\n },\n {\n type: \"section\",\n text: {\n type: \"mrkdwn\",\n text: `*Error in node:* ${errorLog.nodeName}\\n*Message:* ${errorLog.errorMessage}\\n*Run ID:* ${errorLog.runId}\\n*Time:* ${errorLog.timestamp}`\n }\n }\n ]\n };\n \n try {\n await $http.post(config.slackWebhookUrl, {\n body: slackError,\n headers: { 'Content-Type': 'application/json' }\n });\n } catch (notifyError) {\n console.error('Failed to send Slack notification:', notifyError);\n }\n}\n\n// Write to error log sheet if configured\nif (config.masterSheetId) {\n return errorLog;\n}\n\n// Return error for further processing\nreturn { error: errorLog, handled: true };"
},
"typeVersion": 2
},
{
"id": "82668ba0-bdee-4df3-9407-b250cd75cb90",
"name": "CRM Data Processing Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-256,
-96
],
"parameters": {
"text": "You are a CRM Data Processing Expert. Your task is to:\n\n1. **Analyze the incoming CRM data** from multiple sources (HubSpot, Pipedrive, Salesforce)\n2. **Use the pandas MCP tools** to:\n - Calculate data quality scores for each record\n - Perform advanced deduplication using similarity matching\n - Merge duplicate records intelligently\n - Generate data cleansing reports\n\n3. **Process the data** by:\n - Loading the CRM data into pandas for analysis\n - Running deduplication algorithms on email, company name, and phone\n - Calculating quality metrics based on completeness and accuracy\n - Creating merged master records from duplicates\n\n4. **Return structured results** with:\n - Deduplicated dataset\n - Quality scores per record\n - Merge history tracking\n - Data quality report summary\n\nThe input data structure contains: runId, timestamp, totalRecords, breakdown (by source), errors, and data array with records containing: source, recordId, firstName, lastName, email, companyName, phone, stage, lastModified, rawData.\n\nProcess this data thoroughly and return clean, deduplicated CRM records ready for database insertion.",
"options": {},
"promptType": "define"
},
"typeVersion": 2.1
},
{
"id": "0bdfa603-c570-49a0-949a-d3320d8097f1",
"name": "pandas-mcp-server",
"type": "@n8n/n8n-nodes-langchain.mcpClientTool",
"position": [
-32,
112
],
"parameters": {
"sseEndpoint": "http://localhost:8000"
},
"typeVersion": 1
},
{
"id": "d3a13c75-6461-4ee7-bfe0-c525119a419c",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-256,
80
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini",
"cachedResultName": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "d0b1fe2d-c480-42c2-9bbf-adc0734e8456",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1520,
-832
],
"parameters": {
"color": 3,
"width": 560,
"height": 640,
"content": "\ud83d\udee0\ufe0f Multi-CRM Data Sync & AI Deduplication\n\nThis workflow consolidates contact data from HubSpot, Pipedrive, and Salesforce into a unified Google Sheets database with AI-powered deduplication and quality scoring.\n\n\u2705 **Step 1: Configure Environment & Credentials**\n- Set HUBSPOT_API_KEY, PIPEDRIVE_API_KEY, SALESFORCE_ACCESS_TOKEN in environment\n- Add OPENAI_API_KEY for AI processing capabilities\n- Set SLACK_WEBHOOK_URL for notifications\n\n\u2705 **Step 2: Setup Google Sheets Database**\n- Create master Google Sheet with \"Master_CRM_Data\" and \"Quality_Reports\" tabs\n- Set MASTER_SHEET_ID in Configuration Center\n- Grant service account \"Editor\" access to your sheet\n\n\u2705 **Step 3: Configure MCP Server for AI Processing**\n- Install pandas-capable MCP server (or use Code node alternative)\n- Set MCP_SERVER_ENDPOINT in environment (default: http://localhost:8000)\n- Configure AI model credentials for data processing\n\n\u2705 **Step 4: Customize Data Processing Settings (Optional)**\n- Update qualityThreshold (0.7 default) for duplicate detection sensitivity\n- Modify deduplicationKeys for additional matching fields\n- Adjust batchSize based on your API rate limits\n\n\ud83e\uddea **Final Step: Test Complete System**\nTrigger manually via webhook to verify CRM connections, AI processing, and Google Sheets integration work properly"
},
"typeVersion": 1
},
{
"id": "4efb80f1-7722-47fd-8a4e-1225fb5a1116",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-32,
-768
],
"parameters": {
"width": 464,
"height": 608,
"content": "\ud83d\udcca Google Sheets Configuration\n\n**Sheet 1: \"Master_CRM_Data\"**\nAuto-populated Headers:\n- source - CRM system origin (HubSpot/Pipedrive/Salesforce)\n- recordId - Original CRM record identifier\n- firstName - Contact first name\n- lastName - Contact last name \n- email - Primary email address (deduplication key)\n- companyName - Organization name (deduplication key)\n- phone - Phone number (deduplication key)\n- stage - Sales pipeline stage\n- lastModified - Last update timestamp\n- dataQualityScore - AI-calculated quality metric (0-1)\n- isDuplicate - Boolean flag for merged records\n\n\n\ud83d\udd17 Service Account Permissions:\nGrant \"Editor\" access to your Google service account for sheet"
},
"typeVersion": 1
},
{
"id": "d9d7a768-5f00-4a5f-9bca-e47e63537376",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
608,
-416
],
"parameters": {
"color": 6,
"width": 512,
"height": 496,
"content": "\ud83d\udcca Google Sheets Configuration\n\n**Sheet 2: \"Quality_Reports\"**\nAuto-populated Headers:\n- runId - Unique execution identifier\n- timestamp - Sync completion time\n- totalRecords - Count of processed records\n- duplicatesFound - Number of merged duplicates\n- averageQuality - Mean quality score across all records\n- topIssues - Most common data quality problems\n\n\ud83d\udd17 Service Account Permissions:\nGrant \"Editor\" access to your Google service account for both sheets"
},
"typeVersion": 1
},
{
"id": "52b53665-89ec-488a-afe0-647d6d66b664",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-944,
-832
],
"parameters": {
"color": 5,
"width": 528,
"height": 640,
"content": "\ud83d\udd27 Required MCP Servers\n\n\ud83d\udcc2GitHub: [pandas-mcp-server](https://github.com/marlonluo2018/pandas-mcp-server)\n\n\ud83d\udccb Purpose: Advanced data deduplication and quality analysis\n\n**What it does:** Handles complex pandas operations for record matching and data cleansing\n\n**Installation:**\n1. **Clone:** `git clone https://github.com/marlonluo2018/pandas-mcp-server.git`\n2. **Navigate:** `cd pandas-mcp-server`\n3. **Install:** `pip install -r requirements.txt`\n4. **Start:** `python server.py`\n\n**Alternative Setup (No MCP Required):**\nReplace AI Agent with Code node containing pandas logic\nUse standard HTTP Request nodes for CRM APIs\nImplement deduplication logic directly in JavaScript\n\n**Default Configuration:**\n- MCP Server: http://localhost:8000"
},
"typeVersion": 1
},
{
"id": "0e0da7b2-ec42-48bd-b3b6-68e2db46b5da",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1168,
208
],
"parameters": {
"color": 4,
"width": 576,
"height": 256,
"content": "## \ud83d\udea8 Error Management System"
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "2d0b2e3a-2c29-470a-802a-bdc62f367239",
"connections": {
"Error Handler": {
"main": [
[
{
"node": "Error Processor",
"type": "main",
"index": 0
}
]
]
},
"Trigger Router": {
"main": [
[
{
"node": "Configuration Center",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "CRM Data Processing Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"pandas-mcp-server": {
"ai_tool": [
[
{
"node": "CRM Data Processing Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Daily Sync Schedule": {
"main": [
[
{
"node": "Trigger Router",
"type": "main",
"index": 0
}
]
]
},
"Manual Sync Webhook": {
"main": [
[
{
"node": "Trigger Router",
"type": "main",
"index": 1
}
]
]
},
"Configuration Center": {
"main": [
[
{
"node": "Parallel CRM Fetcher",
"type": "main",
"index": 0
}
]
]
},
"Parallel CRM Fetcher": {
"main": [
[
{
"node": "CRM Data Processing Agent",
"type": "main",
"index": 0
}
]
]
},
"Master Database Writer": {
"main": [
[
{
"node": "Quality Report Generator",
"type": "main",
"index": 0
}
]
]
},
"Quality Report Generator": {
"main": [
[
{
"node": "Report Writer",
"type": "main",
"index": 0
}
]
]
},
"CRM Data Processing Agent": {
"main": [
[
{
"node": "Master Database Writer",
"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.
googleApiopenAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
This workflow contains community nodes that are only compatible with the self-hosted version of n8n.
Source: https://n8n.io/workflows/6598/ — original creator credit. Request a take-down →
Related workflows
Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
This workflow automates lead ingestion from Google Sheets and Telegram, leveraging Gemini AI and Lusha for intelligent matching and deep data enrichment. By normalizing incoming data into a standard s
HubSpot, Telegram Trigger, Google Gemini +4
This workflow is designed for B2B/SaaS teams who want to secure renewals before it’s too late.
HTTP Request, Zendesk, Postgres +7
This workflow extracts Lead and Opportunity data from Salesforce, transforms and normalizes the data, and loads it into PostgreSQL as a structured data bank for reporting and analytics.
Salesforce, Postgres
Short Description
N8N Nodes Netsuite Rest, Salesforce
This n8n template automatically enriches company records in your CRM using CompanyEnrich and keeps your data up to date without manual work.
HTTP Request, HubSpot, Salesforce