Multi-channel workflow error alerts with Telegram, Gmail & messaging apps
The Error Notification workflow is designed to instantly notify you whenever any other n8n workflow encounters an error, using popular communication channels like Telegram and Gmail—with optional support for Discord, Slack, and WhatsApp.
💡 Why Use Error Notification workflow?
- Immediate Awareness: Get instant alerts when workflows fail, preventing unnoticed errors and downtime.
- Multi-Channel Flexibility: Notify your team via Telegram, Gmail, and optionally Slack, Discord, or WhatsApp.
- Detailed Context: Receive rich error information including the error message, node name, time, and execution link for quicker fixes.
- Easy Integration: Built with native n8n nodes and customizable code, simple to adopt without complex setup.
- Open Source & Free: Use and adapt this workflow at no cost, making professional error monitoring accessible.
⚡ Who Is This For?
- n8n Workflow Developers: Quickly spot and respond to automation issues in development or production.
- Operations Teams: Maintain uptime and swiftly troubleshoot errors across multiple workflows.
- Small to Medium Businesses: Gain professional error alerting without expensive monitoring tools.
- Automation Enthusiasts: Enhance your automation reliability with real-time failure notifications.
❓ What Problem Does It Solve?
This workflow embedd error detection and notification directly within your n8n instance. It automates the process of catching errors as they occur, compiling meaningful context, and delivering it instantly via your preferred messaging platforms. This drastically reduces your response time to issues and streamlines error management, improving your automation reliability and operational confidence.
🔧 What This Workflow Does
⏱ Trigger: Listens for any error generated in your n8n workflows using the n8n Error Trigger node.
📎 Step 2: Executes a Code node that formats a detailed error message capturing workflow name, error node, description, timestamp, and an execution URL.
🔍 Step 3: Sends the formatted error notification to multiple communication channels: Telegram and Gmail by default, plus optionally Discord, Slack, and WhatsApp (disabled by default).
💌 Step 4: Delivers rich, parsed HTML-formatted messages to ensure error readability and immediate actionability.
🔐 Setup Instructions
-
Import the provided
.jsonfile into your n8n instance (Cloud or self-hosted). -
Set up credentials:
- Gmail OAuth credentials for sending emails via Gmail node
- Telegram API credentials for Telegram notifications
- (Optional) Discord Webhook URL credential for Discord notifications
- (Optional) Slack Webhook credential for Slack notifications
- (Optional) WhatsApp connection credentials (if enabled)
-
Customize the Code node if needed to adjust the error message format or target chat IDs.
-
Update the chat IDs and recipient details in each notification node according to your channels.
-
Test the workflow by manually triggering an error in another workflow to verify proper notifications.
🧩 Pre-Requirements
- Active n8n instance (cloud or self-hosted) with version supporting Error Trigger node
- Telegram bot credentials and chat ID
- (Optional) Gmail, Discord, Slack, or WhatsApp accounts and webhook credentials if you want to use those channels
🛠️ Customize It Further
- Enable and configure additional notification nodes like Slack or WhatsApp to fit your team's communication style.
- Customize the error message template in the Code node to include extra metadata or format it differently (e.g., markdown).
- Integrate with incident management tools via webhook nodes or create tickets automatically on error.
🧠 Nodes Used
- Error Trigger
- Code
- Telegram
- Gmail
- Discord (disabled)
- Slack (disabled)
- WhatsApp (disabled)
- Sticky Note (for description)
📞 Support
Made by: khaisa Studio
Tag: notification,error,monitoring,workflow,automation,alerts
Category: Monitoring & Alerts
Need a custom? Need a custom? contact me on LinkedIn or Web
n8n Multi-Channel Workflow Error Alerts
This n8n workflow provides a robust system for handling workflow execution errors by sending alerts to multiple communication channels. It acts as a centralized error notification system, ensuring that critical workflow failures are immediately brought to the attention of relevant stakeholders through their preferred messaging platforms and email.
What it does
This workflow is designed to be triggered whenever another n8n workflow encounters an error. Upon activation, it performs the following actions:
- Listens for Errors: The workflow starts with an "Error Trigger" node, which automatically activates when any other workflow on the n8n instance fails.
- Generates Error Summary: A "Code" node processes the incoming error data to extract key details such as the workflow name, error message, and execution ID, formatting them into a human-readable message.
- Sends Slack Notification: It posts a detailed error alert to a designated Slack channel, providing immediate visibility to teams using Slack for communication.
- Sends Telegram Notification: It dispatches the error message to a specified Telegram chat or channel, catering to users who prefer Telegram for alerts.
- Sends Discord Notification: It sends an error notification to a Discord channel, useful for development teams or communities that use Discord.
- Sends Gmail Email: It composes and sends an email via Gmail containing the error details to a predefined recipient list, ensuring that email-centric teams are also informed.
- Sends WhatsApp Business Cloud Message: It sends an error message through WhatsApp Business Cloud, offering a direct and widely used mobile messaging channel for critical alerts.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n Instance: An active n8n instance where this workflow will be imported.
- Slack Account: A Slack workspace and a channel where error notifications should be posted. You'll need to configure Slack credentials in n8n.
- Telegram Account: A Telegram bot and a chat ID or channel ID to which messages will be sent. Telegram credentials need to be set up in n8n.
- Discord Account: A Discord server and a channel webhook URL. Discord credentials need to be configured in n8n.
- Gmail Account: A Google account with Gmail enabled to send email alerts. You'll need to configure Gmail OAuth credentials in n8n.
- WhatsApp Business Cloud Account: An active WhatsApp Business Cloud account with a configured phone number and a recipient phone number for alerts. WhatsApp credentials need to be set up in n8n.
Setup/Usage
- Import the workflow: Download the provided JSON and import it into your n8n instance.
- Configure Credentials:
- For each of the communication nodes (Slack, Telegram, Discord, Gmail, WhatsApp Business Cloud), you will need to set up the respective credentials in n8n. Follow the n8n documentation for each service to correctly configure API keys, OAuth tokens, or webhooks.
- Customize Notification Details (Code Node):
- Open the "Code" node and review the JavaScript code. You can customize the message format or add/remove specific error details that are extracted.
- Configure Recipient Details:
- Slack: In the "Slack" node, specify the
Channelwhere the messages should be posted. - Telegram: In the "Telegram" node, specify the
Chat IDto which the messages should be sent. - Discord: In the "Discord" node, ensure the
Webhook URLis correctly set for your desired channel. - Gmail: In the "Gmail" node, specify the
Toemail address(es) for the alerts. - WhatsApp Business Cloud: In the "WhatsApp Business Cloud" node, specify the
Phone Number IDand theTorecipient phone number.
- Slack: In the "Slack" node, specify the
- Activate the Workflow: Once all credentials and configurations are in place, activate the workflow.
- Link to Error Workflows: In any workflow where you want to receive error alerts, go to the workflow settings and set this workflow as the "Error Workflow". This will ensure that if that workflow fails, it triggers this multi-channel alert system.
Related Templates
Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax
Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions
Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation
PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive ➜ Download PDF ➜ OCR text ➜ AI normalize to JSON ➜ Upsert Buyer (Account) ➜ Create Opportunity ➜ Map Products ➜ Create OLI via Composite API ➜ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content → the parsed JSON (ensure it’s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id ➜ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total ➜ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger → Download File From Google Download File From Google → Extract from File → Update File to One Drive Extract from File → Message a model Message a model → Create or update an account Create or update an account → Create an opportunity Create an opportunity → Build SOQL Build SOQL → Query PricebookEntries Query PricebookEntries → Code in JavaScript Code in JavaScript → Create Opportunity Line Items --- Quick setup checklist 🔐 Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. 📂 IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) 🧠 AI Prompt: Use the strict system prompt; jsonOutput = true. 🧾 Field mappings: Buyer tax id/name → Account upsert fields Invoice code/date/amount → Opportunity fields Product name must equal your Product2.ProductCode in SF. ✅ Test: Drop a sample PDF → verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep “Return only a JSON array” as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields don’t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your org’s domain or use the Salesforce node’s Bulk Upsert for simplicity.