Workflow Templates

How it works This template is an interactive playground designed to help you master the most useful keyboard shortcuts in n8n and supercharge your building speed. Forget boring lists—this workflow gives you hands-on tasks to complete, turning learning into a practical exercise. The workflow is structured into four chapters, each focusing on a different aspect of workflow development: Node Basics: Learn the fundamentals of interacting with a single node, such as renaming, editing, duplicating, and deactivating. Canvas Navigation & Selection: Master the art of moving around the canvas and selecting multiple nodes efficiently. Advanced Actions: Discover powerful moves like tidying up messy connections and creating sub-workflows. Execution & Debugging: Uncover essential shortcuts for testing your workflows, like pinning data and navigating the executions panel. Each step provides a clear task in a sticky note, guiding you to perform the action yourself. Set up steps Setup time: 0 minutes! This workflow is a self-contained tutorial and requires no setup, credentials, or configuration. Open the workflow. Follow the instructions in the sticky notes, starting from the top. Perform the actions as described to build muscle memory for each shortcut. That's it! Get ready to become an n8n power user.

This n8n workflow automates the process of parsing and extracting data from PDF invoices. With this workflow, accounts and finance people can realise huge time and cost savings in their busy schedules. Read the Blog: https://blog.n8n.io/how-to-extract-data-from-pdf-to-excel-spreadsheet-advance-parsing-with-n8n-io-and-llamaparse/ How it works This workflow will watch an email inbox for incoming invoices from suppliers It will download the attached PDFs and processing them through a third party service called LlamaParse. LlamaParse is specifically designed to handle and convert complex PDF data structures such as tables to markdown. Markdown is easily to process for LLM models and so the data extraction by our AI agent is more accurate and reliable. The workflow exports the extracted data from the AI agent to Google Sheets once the job complete. Requirements The criteria of the email trigger must be configured to capture emails with attachments. The gmail label "invoice synced" must be created before using this workflow. A LlamaIndex.ai account to use the LlamaParse service. An OpenAI account to use GPT for AI work. Google Sheets to save the output of the data extraction process although this can be replaced for whatever your needs. Customizing this workflow This workflow uses Gmail and Google Sheets but these can easily be swapped out for equivalent services such as Outlook and Excel. Not using Excel? Simple redirect the output of the AI agent to your accounting software of choice.

This n8n workflow takes Slack conversations and turns them into Calendar events complete with accurate date and times and location information. Adding and removing attendees are also managed automatically. How it works Workflow monitors a Slack channel for invite messages with a "📅" reaction and sends this to the AI agent. AI agent parses the message determining the time, date and location. Using its Location tool, the AI agent searches for the precise location address from Google Maps. Using its Calendar tool, the AI agent creates a Google Calendar invite with the title, description and location address for the user. Back in the Slack channel, others can RSVP to the invite by reacting with the "✅" emjoi. The workflow polls the message after a while and adds the users who have reacted to the Calendar Invite as attendees. Conversely, removing any attendees who have since removed their reaction. Examples Jill: "Hey team, I'm organising a round of Laser Tag (Bunker 51) next Thursday around 6pm. Please RSVP with a ✅" AI: "I've helped you create an event in your calendar https://cal.google.com/..." Jack: "✅" AI: "I've added Jack to the event as an attendee". Requirements Slack channel to attach the workflow OpenAI account to use a GPT model Google Calendar to create and update events Customising the Workflow This workflow can work with other messaging platforms that support reactions or tagging like features such as discord. Don't use Google Calendar? Swap it out for Outlook or your own. Use any combinations of emjoi reactions and add new rules like "RSVP maybe" which could send reminder updates nearer the event date.

This n8n template automates triaging of newly opened support tickets and issue resolution via JIRA. If your organisation deals with a large number of support requests daily, automating triaging is a great use-case for introducing AI to your support teams. Extending the idea, we can also get AI to give a first attempt at resolving the issue intelligently. How it works A scheduled trigger picks up newly opened JIRA support tickets from the queue and discards any seen before. An AI agent analyses the open ticket to add labels, priority on the seriousness of the issue and simplifies the description for better readability and understanding for human support. Next, the agent attempts to address and resolve the issue by finding similar issues (by tags) which have been resolved. Each similar issue has its comments analysed and summarised to identify the actual resolution and facts. These summarises are then used as context for the AI agent to suggest a fix to the open ticket. How to use Simply connect your JIRA instance to the workflow and activate to start watching for open tickets. Depending on frequency, you may need to increase for decrease the intervals. Define labels to use in the agent's system prompt. Restrict to certain projects or issue types to suit your organisation. Requirements JIRA for issue management and support portal OpenAI for LLM Customising this workflow Not using JIRA? Try swapping out the nodes for Linear or your issue management system of choice. Try a different approach for issue resolution. You might want to try RAG approach where a knowledge base is used.

Who’s it for This template is built for founders, sales teams, agencies, consultants, and growth operators who want a fully automated way to discover high-intent companies showing buying signals such as funding, hiring, launches, or expansion — without manual research. It’s ideal for outbound sales, partnership scouting, market intelligence, and lead generation. What it does / How it works This workflow automates daily business signal monitoring and opportunity detection. It runs on a daily schedule and collects data from multiple sources: LinkedIn** X** Product Hunt** CrunchBase** Google News** All incoming data is: Merged and normalized into a single unified feed Cleaned and deduplicated Passed to an AI agent powered by Google Gemini The AI agent: Filters only relevant events (Funding, Launch, Expansion, Hiring) Generates a concise summary Explains why the event represents a business opportunity Based on the AI classification: Relevant opportunities continue through the workflow Irrelevant noise is automatically discarded For each qualified opportunity: Company/contact data is enriched via an external API The opportunity is saved to Google Sheets A real-time alert is sent via Telegram All logic runs automatically end-to-end. Requirements Google News (NewsAPI) API key Twitter/X API credentials Product Hunt API credentials Crunchbase RSS feed access Google Sheets OAuth2 credentials Telegram Bot credentials Google Gemini (PaLM) API credentials (Optional) Contact enrichment API How to set up Import the workflow into n8n. Connect all required credentials: Google Gemini Google Sheets Telegram External APIs (News, X, Product Hunt) Replace placeholders: Google Sheet ID and range Telegram Chat ID Enrichment API URL (if used) Adjust search queries if needed. Run the workflow once manually to test. Enable the Daily Trigger to activate automation. How to customize the workflow Modify AI prompts to refine opportunity criteria Add new data sources (LinkedIn, Reddit, Hacker News) Change schedule frequency (hourly, weekly) Log opportunities into a CRM instead of Sheets Add email or Slack alerts Expand enrichment logic for deeper company insights This workflow transforms scattered startup news into a clean, daily stream of actionable business opportunities — fully automated.

Automatically create Google Tasks from new Gmail emails labeled "To-Do". Who is this for? This template is perfect for individuals and teams who want to boost their productivity by automatically converting important emails into actionable tasks in Google Tasks. What problem is this workflow solving? Manually managing emails and creating tasks can be tedious. This workflow ensures you never miss a follow-up by instantly turning important emails into tasks without switching between apps. What this workflow does? Watches for new emails in Gmail with the label "To-Do". Creates a new Google Task with the email subject as the task title and the email snippet as notes. Sets the task due date to 24 hours after the email is received. Setup Create a label "To-Do" in your Gmail account if it doesn't already exist. Connect your Gmail and Google Tasks accounts to n8n using OAuth2 credentials. Import the workflow into n8n and activate it. How to customize this workflow to your needs? Change the Gmail label to a different one (e.g., "Important", "Follow-up"). Modify the due date logic in the expression if you want more/less time to complete tasks: {{ $now.add(2, 'days').toISOString() }} Add additional Gmail filters (like only unread emails) to refine which emails create tasks.

🔄 Reddit Content Operations via MCP Server 🧑‍💼 Who is this for? This workflow is built for content creators, marketers, Reddit automation enthusiasts, and AI agent developers who want structured, programmable access to Reddit content. If you're researching niche communities, tracking trends, or automating Reddit engagement — this is for you. 💡 What problem is this workflow solving? Reddit has valuable content scattered across subreddits, but manual analysis or engagement is inefficient. This workflow acts as a centralized API interface to: Query and manage Reddit posts Create, fetch, delete, and reply to comments Analyze subreddit metadata and behavior Enable AI agents to autonomously operate on Reddit data It does this using an MCP (Model Context Protocol) Server over Server-Sent Events (SSE). ⚙️ What this workflow does This template sets up a custom MCP Server that listens for JSON-based operation commands sent via SSE. Based on the operation, it routes the request to one of the following branches: 🟥 Post CRUD Create a new Reddit post Search posts across subreddits Fetch posts by ID Delete existing posts 🟩 Comment CRUD Create or reply to comments Fetch multiple comments from posts Delete specific comments 🟦 Subreddit Read Operations Get information about subreddits List subreddit posts Retrieve subreddit rules 🛠 Setup Import this workflow into your self-hosted n8n instance. Configure Reddit credentials (OAuth2). Connect your input system to the MCP Server Trigger node via SSE. Send operation payloads to the server like this: { "operation": "post_search", "params": { "query": "AI agents", "subreddit": "machinelearning" } } The workflow will route to the appropriate node based on operation type. 🧩 Supported Operations post_create post_get_many post_search post_delete post_get_by_id comment_create comment_reply comment_get_many comment_delete subreddit_get_about subreddit_get_many subreddit_get_rules 🧠 How to customize this workflow to your needs Add new operations to the operation_switch node for additional API functionality. Chain results into Notion, Slack, Airtable, or external APIs. Integrate with OpenAI/GPT to summarize posts or filter content. Add logic to score and sort content by engagement, sentiment, or keywords. 🟨 Sticky Notes Each operation group is color-coded (Posts, Comments, Subreddits). Sticky Notes explain the purpose and dependencies of each section. Easy to maintain and extend with clear logical separation. ⚠️ This template uses a custom MCP Server node and only works in self-hosted n8n. 🖼 Workflow Preview

🚀 What this flow does • 🔎 Selects the least-used WordPress category (tracked in PostgreSQL) • 🤖 Uses GPT (4-mini or better) to generate a fully formatted SEO article with headings, TOC, lists, CTA, and Yoast blocks • 🖼️ Creates a placeholder cover image and uploads it to WordPress Media • 📬 Publishes the final post via /wp-json/wp/v2/posts with correct category + featured image • 🧠 Logs the used category for future rotation (zero duplicates!) ⚙️ Setup in 3 mins 🏷️ Add your WordPress domain with a simple Set node:     domain=https://yourdomain.com 🔐 Create these 3 credentials in n8n:     YOUR_WORDPRESS_CREDENTIAL — for /media, /posts     YOUR_POSTGRES_CREDENTIAL — for category tracking     YOUR_OPENAI_CREDENTIAL — GPT-4-mini or better 🧱 Run the SQL from docs to create the used_categories table ✅ Manually test first 3–5 nodes to check WP auth, OpenAI response, and DB connection 🕒 Then just schedule it and let the bot write for you. 🎯 Why it's awesome This is your personal AI content writer + publisher — perfect for: • 📰 SEO content farms • 📈 Affiliate blogs • 🧰 Micro niche sites • 🤫 PBNs with rotation-safe automation No more manual uploads, broken categories, or GPT spam. Every post is structured, beautiful, and intelligently categorized.

This workflow automates sentiment analysis of Reddit posts related to Apple's WWDC25 event. It extracts data, categorizes posts, analyzes sentiment of comments, and updates a Google Sheet with the results. Preliquisites Bright Data Account: You need a Bright Data account to scrape Reddit data. Ensure you have the correct permissions to use their API. https://brightdata.com/ Google Sheets API Credentials: Enable the Google Sheets API in your Google Cloud project and create credentials (OAuth 2.0 Client IDs). Google Gemini API Credentials: You need a Gemini API key to run the sentiment analysis. Ensure you have the correct permissions to use their API. https://ai.google.dev/". You can use any other models of choice Setup Import the Workflow: Import the provided JSON workflow into your n8n instance.", Configure Bright Data Credentials:, In the 'scrap reddit' and the 'get status' nodes, in Header Parameters find the Authorization field, replace Bearer 1234 with your Bright Data API key. Apply this to every node that utilizes your Bright Data API Key., Set up the Google Sheets API credentials, In the 'Append Sentiments' node, set up the Google Sheets API by connecting your Google Sheets account through oAuth 2 credentials. ", Configure the Google Gemini Credential ID, In the ' Sentiment Analysis per comment' node, set up the Google Gemini API by connecting your Google AI account through the API credentials. , Configure Additional Parameters:, In the 'scrap reddit' node, modify the JSON body to adjust the search term, date, or sort method., In the 'Wait' node, alter the 'Amount' to adjust the polling interval for scraping status, it is set to 15 seconds by default., In the 'Text Classifier' node, customize the categories and descriptions to suit the sentiment analysis needs. Review categories such as 'WWDC events' to ensure relevancy., In the 'Sentiment Analysis per comment' node, modify the system prompt template to improve context. customization_options Bright Data API parameters to adjust scraping behavior. Wait node duration to optimize polling. Text Classifier categories and descriptions. Sentiment Analysis system prompt. Use Case Examples Brand Monitoring:** Track public sentiment towards Apple during and after the WWDC25 event. Product Feedback Analysis:** Gather insights into user reactions to new product announcements. Competitive Analysis:** Compare sentiment towards Apple's announcements versus competitors. Event Impact Assessment:** Measure the overall impact of the WWDC25 event on various aspects of Apple's business. Target_audiences: Marketing professionals in the tech industry, Brand managers, Product managers, Market research analysts, Social media managers Troubleshooting: Workflow fails to start. Check that all necessary credentials (Bright Data and Google Sheets API) are correctly configured and that the Bright Data API key is valid. Data scraping fails. Verify the Bright Data API key, ensure the dataset ID is correct, and inspect the Bright Data dashboard for any issues with the scraping job. Sentiment analysis is inaccurate. Refine the categories and descriptions in the 'Text Classifier' node. Check that you have the correct Google Gemini API key, as the original is a placeholder. Google Sheets are not updating. Ensure the Google Sheets API credentials have the necessary permissions to write to the specified spreadsheet and sheet. Check API usage limits. Workflow does not produce the correct output. Check the data connections, by clicking the connections, and looking at which data is being produced. Check all formulas for errors. Happy productivity!

Stay on top of the latest crypto news and market sentiment instantly, all inside Telegram! This workflow aggregates articles from the top crypto news sources, filters for your topic of interest, and summarizes key news and market sentiment using GPT-4o AI. Ideal for crypto traders, investors, analysts, and market watchers needing fast, intelligent news briefings. > 💬 Just type a coin name (e.g., "Bitcoin", "Solana", "DeFi") into your Telegram AI Agent—and get a smart news digest. How It Works Telegram Bot Trigger User sends a keyword (e.g., "Ethereum") of questions to the Telegram AI Agent. Keyword Extraction (AI-Powered) An AI agent identifies the main topic for better targeting. News Aggregation Pulls articles from 9 major crypto news RSS feeds: Cointelegraph Bitcoin Magazine CoinDesk Bitcoinist NewsBTC CryptoPotato 99Bitcoins CryptoBriefing Crypto.news Filtering Finds and merges articles relevant to the user's keyword. AI Summarization GPT-4o generates a 3-part summary: News Summary Market Sentiment Analysis List of Article Links Telegram Response Sends a structured, easy-to-read digest back to the user. 🔍 What You Can Do with This Workflow 🔹 Summarize breaking news for any crypto project or keyword 🔹 Monitor real-time market sentiment on Bitcoin, DeFi, NFTs, and more 🔹 Stay ahead of FUD, bullish trends, and major news events 🔹 Quickly brief yourself or your team via Telegram 🔹 Use it as a foundation for more advanced crypto alert bots ✅ Example User Inputs ✅ "Bitcoin" → Latest Bitcoin news and sentiment summary ✅ "Solana" → Updates on Solana projects, price movements, and community trends ✅ "NFT" → Aggregated news about NFT markets and launches ✅ "Layer 2" → Insights on Optimism, Arbitrum, and other L2s 🛠️ Setup Instructions Create a Telegram Bot Use @BotFather and obtain the Bot Token. Configure Telegram Credentials in n8n Add your bot token under Telegram API Credentials. Configure OpenAI API Add your OpenAI credentials for GPT-4o access. Update Telegram Send Node In the Telegram Send node, replace the placeholder chatId with your real Telegram user or group chat ID. Deploy and Test Start chatting with your bot: e.g., "Ethereum" or "DeFi". 📌 Workflow Highlights 9 major crypto news sources combined** Smart keyword matching** with AI query parsing Summarized insights** in human-readable format Reference links** included for deeper reading Instant delivery** via Telegram 🚀 Get ahead of the crypto market—automate your news and sentiment monitoring with AI inside Telegram!

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: retrieved document relevance (i.e. whether the information retrieved from a vector store is relevant to the question). The workflow takes a question and checks whether the information retrieved to answer it is relevant. To run this workflow, you need to insert documents into a vector data store, so that they can be retrieved by the agent to answer questions. You can do this by running the top part of the workflow once. The main workflow works as follows: We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular trigger so that the workflow can be started from either one. More info We make sure that the agent outputs the list data from the tools that it used If we’re evaluating (i.e. the execution started from the evaluation trigger), we calculate the relevance metric using AI to compare the retrieved documents with the question We pass this information back to n8n as a metric If we’re not evaluating we avoid calculating the metric, to reduce cost

This workflow automates the creation and management of a Retrieval-Augmented Generation (RAG) system using Qdrant as a vector store and Google Drive as the document source. It enables full or incremental updates to documents in the Qdrant vector database and integrates with a chatbot using Google Gemini for question answering. Here is a clear and professional description in English of the n8n workflow “Create a RAG with Qdrant and update single files”, including its benefits: Benefits Efficient RAG Setup** Seamlessly integrates OpenAI, Qdrant, and Google Drive to create a scalable RAG pipeline. Single File Update** You can replace the vector representation of a single file without reprocessing the entire collection—ideal for maintaining document freshness. Flexible File Source** Works with Google Drive, allowing document management and updates from a familiar interface. How It Works This workflow is designed to create a Retrieval-Augmented Generation (RAG) system using Qdrant as a vector store and Google Drive as a document source. It consists of four main phases: Collection Setup**: Creates or clears a Qdrant collection to store vectorized documents. Configures the collection with cosine distance metrics and other parameters. Document Processing**: Retrieves files from a specified Google Drive folder. Downloads and processes each file (text extraction, chunking, and embedding using OpenAI). Stores the embeddings in Qdrant for vector search. Single-File Update**: Allows updating or deleting a specific file in the Qdrant collection by referencing its Google Drive ID. Re-embeds the file and updates the vector store. RAG Querying**: Uses a chat trigger to receive user questions. Retrieves relevant documents from Qdrant using vector similarity. Generates answers using Google Gemini as the language model. Set Up Steps Configure Qdrant: Replace QDRANTURL and COLLECTION in the "Create collection" and "Clear collection" HTTP nodes. Ensure Qdrant API credentials are correctly set in the credentials section. Google Drive Integration: Specify the Google Drive folder ID in the "Get files" node. Ensure Google Drive OAuth credentials are configured. OpenAI and Gemini Keys: Add OpenAI API credentials for embeddings (used in "Embeddings OpenAI" nodes). Configure Google Gemini credentials for the chat model. Single-File Update: Set the file_id in the "Edit Fields3" node to target a specific Google Drive file for updates. Testing: Trigger the workflow manually to populate the Qdrant collection. Use the chat interface to test RAG responses. Need help customizing? Contact me for consulting and support or add me on Linkedin.