Workflow Templates

Turn Reddit Questions into SEO Articles Automatically This workflow takes real user questions from Reddit and transforms them into fully structured blog posts — title, intro, steps, and conclusion — using AI. How it works Manually triggered when you want to run it Scrapes the latest posts from a specific subreddit (e.g. r/n8n) Filters only posts that are real questions (based on keywords like “how,” “what,” “why”) Logs relevant questions into a Google Sheet as raw input Enhances each question using AI (rephrases, creates a clean title and slug) Generates full-length blog content: ✏️ Intro paragraph ✅ Step-by-step guide 🧠 Clear conclusion Saves the final blog content to a second Google Sheet for publishing Set up steps You’ll need access to: Reddit API (OAuth) OpenAI API Google Sheets Takes around 15–20 minutes to connect all the credentials and tweak prompts Customize the subreddit or topic focus by changing the Reddit node config Perfect for content teams who want to scale content output using real community pain points — without ever starting from a blank page.

Remixed Backup your workflows to GitHub from Solomon's work. Check out his templates. How it works This workflow will backup your typebots to GitHub. It uses the Typebot API to export all typebots. It then loops over the data, checks in GitHub to see if a file exists that uses the credential's ID. Once checked it will: update the file on GitHub if it exists; create a new file if it doesn't exist; ignore if it's the same. In addition, it also checks if any flow have been deleted from typebot workspace. If a flow no longer exists in workspace, the corresponding file will be removed from the repository to keep everything in sync. Who is this for? People wanting to backup their typebots(flows) outside the server for safety purposes or to migrate to another server.

How it works Automatically sends Telegram notifications when any n8n workflow fails. Includes workflow name, error message, and execution ID in the alert. Setup Complete setup instructions included in the workflow's sticky note in 5 languages: 🇬🇧 English 🇪🇸 Español 🇩🇪 Deutsch 🇫🇷 Français 🇷🇺 Русский Features Monitors all workflows 24/7 Instant Telegram notifications Zero configuration needed Just add your bot token and chat ID Important ⚠️ Keep this workflow active 24/7 to capture all errors.

Who is this template for? This workflow template is ideal for anyone using Notion for project management and Clockify for time tracking. The workflow automatically adds all new clients from Notion to Clockify. How it works Scans your Notion client table every minute for new clients Adds all new clients to your Clockify workspace Set up Steps Set up the Notion trigger node by adding your Notion API credentials as described in the n8n Notion docs. Go to your Notion clients page/table and give your integration permission to acces the data on this page. Go back to n8n and select your Notion client page in the Notion trigger node. Set up the Clockify node by adding your Clockify API credentials as described in the n8n Clockify docs, select your Clockify workspace and map your client name column from Notion to the Clockify "Client Name" field.

Purpose This workflow adds the capability to build a RAG on living data. In this case Notion is used as a Knowledge Base. Whenever a page is updated, the embeddings get upserted in a Supabase Vector Store. It can also be fairly easily adapted to PGVector, Pinecone, or Qdrant by using a custom HTTP request for the latter two. Demo How it works A trigger checks every minute for changes in the Notion Database. The manual polling approach improves accuracy and prevents changes from being lost between cached polling intervals. Afterwards every updated page is processed sequentially The Vector Database is searched using the Notion Page ID stored in the metadata of each embedding. If old entries exist, they are deleted. All blocks of the Notion Database Page are retrieved and combined into a single string The content is embedded and split into chunks if necessary. Metadata, including the Notion Page ID, is added during storage for future reference. A simple Question and Answer Chain enables users to ask questions about the embedded content through the integrated chat function Prerequisites To setup a new Vector Store in Supabase, follow this guide Prepare a simple Database in Notion with each Database Page containing at least a title and some content in the blocks section. You can of course also connect this to an existing Database of your choice. Setup Select your credentials in the nodes which require those If you are on an n8n cloud plan, switch to the native Notion Trigger by activating it and deactivating the Schedule Trigger along with its subsequent Notion Node Choose your Notion Database in the first Node related to Notion Adjust the chunk size and overlap in the Token Splitter to your preference Activate the workflow How to use Populate your Notion Database with useful information and use the chat mode of this workflow to ask questions about it. Updates to a Notion Page should quickly reflect in future conversations.

Multi-Agent Book Creation Workflow with AI Tool Node and GPT-4, DALL-E Who’s it for This workflow is designed for: Content creators** who want to generate books or structured documents automatically. Educators and trainers** who need quick course materials, eBooks, or study guides. Automation enthusiasts* exploring *multi-agent systems* using the newly released *AI Tool Node** in n8n. Developers* looking for a reference template to understand *orchestration of multiple AI agents** with structured output. How it works / What it does This template demonstrates a multi-agent orchestration system powered by AI Tool Nodes: Trigger: Workflow starts when a chat message is received. Book Brief Agent: Generates the initial book concept (title, subtitle, and outline). Book Writer Agent: Expands the outline into full content by collaborating with two sub-agents: Designer Agent → Provides layout/design suggestions. Content Writer Agent → Drafts and refines chapters. Generate Cover Image: AI generates a custom book cover image. Upload to AWS S3: Stores the cover image securely. Configure Metadata: Adds metadata for title, author, and description. Build Book HTML: Converts markdown-based content into HTML format. Upload to Google Drive: Saves the HTML content for processing. Convert to PDF: Transforms the book into a professional PDF. Archive to Google Drive: Final version is archived for safe storage. This workflow showcases multi-agent coordination, structured parsing, and seamless integration with cloud storage services. How to set up Import the workflow into n8n. Configure the following connections: OpenAI (for Book Brief, Book Writer, Designer, and Content Writer Agents). AWS S3 (for image storage). Google Drive (for document storage & archiving). Add your API keys and credentials in n8n credentials manager. Test the workflow by sending a sample chat message (e.g., “Write a book about AI in education”). Verify outputs in Google Drive (HTML + PDF) and AWS S3 (cover image). Requirements n8n* (latest version with *AI Tool Node** support). OpenAI API key** (to power multi-agent models). AWS account** (with S3 bucket for storing images). Google Drive integration** (for document storage and archiving). Basic familiarity with workflow setup in n8n. How to customize the workflow Switch Models**: Replace gpt-4.1-mini with other models (faster, cheaper, or more powerful). Add More Agents: Introduce agents for **editing, fact-checking, or translation. Change Output Format: Export to **EPUB, DOCX, or Markdown instead of PDF. Branding Options: Modify the **cover generation prompt to include company logos or specific style. Extend Storage: Add **Dropbox, OneDrive, or Notion integration for additional archiving. Trigger Alternatives: Replace chat trigger with **form submission, webhook, or schedule-based runs. ✅ This workflow acts as a free, plug-and-play template to showcase how multi-agents + AI Tool Node can work together to automate complex content creation pipelines.

This workflow offers several additional features for time tracking with Awork: Check whether time has been tracked when closing a task. If not, the task is reopened and the user is notified. This can be restricted to specific tasks using tags. Enforce a minimum time entry for tasks to comply with "at least 15-minute intervals are billed" policies. This can also be limited to specific tasks by using tags. Clean up time entries to match billing intervals. Add a start time to time entries if it is missing. This workflow does not use the Awork community nodes package, as the package does not support all required API calls and is therefore not used here. If you prefer to use that package, you can find more information at awork integration guide and replace the HTTP nodes with the corresponding community nodes where applicable. How it works Triggered via Awork Webhook call on status change of tasks and new time entries Set up steps Add webhook call to Awork (please see in-workflow notes regarding webhook configuration) Configure Awork API credentials Set up workflow configuration via setup node, e.g. user notification text, tags, enabled features etc.

Complete MCP server exposing all PagerDuty Tool operations to AI agents. Zero configuration needed - all 9 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every PagerDuty Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n PagerDuty Tool tool with full error handling 📋 Available Operations (9 total) Every possible PagerDuty Tool operation is included: 🔧 Incident (4 operations) • Create an incident • Get an incident • Get many incidents • Update an incident 🔧 Incidentnote (2 operations) • Create an incident note • Get many incident notes 🔧 Logentry (2 operations) • Get a log entry • Get many log entries 👤 User (1 operations) • Get a user 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native PagerDuty Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every PagerDuty Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Overview Fetch Multiple Google Analytics GA4 metrics daily, post to Discord, update previous day’s entry as GA data finalizes over seven days. Benefits Automates daily traffic reporting Maintains single message per day, avoids channel clutter Provides near–real-time updates by editing prior messages Use Case Teams tracking website performance via Discord (or any chat tool) without manual copy–paste. Marketing managers, community moderators, growth hackers. If your manager asks you for daily marketing report every morning, you can now automate it Notes google analytics node in n8n does not provide real time data. The node updates previous values for the next 7 days discord node on n8n does not have features to update an exisiting message by message id. So we have used the discord api for this most businesses use multiple google analytics properties across their digital platforms Core Logic Schedule trigger fires once a day. Google Analytics node retrieves metrics for date ranges (past 7 days) Aggregate node collates all records. Discord node fetches the last 10 messages in the broadcast channel Code node maps existing Discord messages by to the google analytics data using the date fields For each GA record: If no message exists → send new POST to the discord channel If message exists and metrics changed, send an update patch to the existing discord message Batch loops + wait nodes prevent rate-limit. Setup Instructions Import workflow JSON into n8n. Follow the n8n guide to Create Google Analytics OAuth2 credential with access to all required GA accounts. Follow the n8n guide to Create Discord OAuth2 credential for “Get Messages” operations. Follow the Discord guide to Create HTTP Header Auth credential named “Discord-Bot” with header Key: Authorization Value: Bot <your-bot-token> In the two Set nodes in the beginning of the flow, assign discord_channel_id and google_analytics_id. Get your discord channel id by sending a text on your discord channel and then copy message link Paste the text below and you will see your message link in the form of https://discord.com/channels/server_id/channel_id/message_id , you will want to get the channel_id which is the number in the middle Find your google analytics id by going to google analytics dashboard, seeing the properties in the top right and copy paste that number to the flow Adjust schedule trigger times to your preferred report hour. Activate workflow. Customization Replace Discord HTTP Request nodes with Slack, ClickUp, WhatsApp, Telegram integrations by swapping POST/PATCH endpoints and authentication.

Complete MCP server exposing 1 Listing API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Listing API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Listing API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.ebay.com{basePath} • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 total) 🔧 Item_Draft (1 endpoints) • POST /item_draft/: Create eBay Listing Draft 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Listing API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Complete MCP server exposing 1 IP2Proxy Proxy Detection API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add IP2Proxy Proxy Detection credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the IP2Proxy Proxy Detection API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.ip2proxy.com • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 total) 🔧 General (1 endpoints) • GET /: Check Proxy IP 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native IP2Proxy Proxy Detection API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Instructions This automation enables you to just upload any Image (via Form) of a Logo Sheet, containing multiple Images of Product Logos (most likely) which brings them in some context to one another. After submitting an AI-Agent eats that Logo Sheet, turning it into an List of "Productname" and "Attributes", also checks if Tools are kind of similar to another, given the Context of the Image. We utilize AI Vision capabilities for that. NOTE: It might not be able to extract all informations. For a "upload and forget it" Workflow it works for me. You can even run it multiple times, to be sure. But if you need to make sure it extracts everything you might need to think about an Multi-Agent Setup with Validation-Agent Steps. Once the Agent finishes the extraction, it will traditionally and deterministicly add those Attributes to Airtable (Creates those, if not already existing.) and also Upserts the Tool Informations. It uses MD5 Hashes for turning Product Names into.. something fancy really, you could also use it without that, but I wanted to have something that looks atleast like an ID. Setup Set Up the Airtable like shown below. Update and set Credentials for all Airtable Nodes. Check or Adjust the Prompt of the Agent matching your use-case. Activate the Workflow. Open the Form (default: https://your-n8n.io/form/logo-sheet-feeder) Enjoy growing your Airtable. Enjoy the workflow! ❤️ let the work flow — Workflow Automation & Development