Workflow Templates

This n8n workflow takes in a document such as a research paper, marketing or sales deck or company filings, and breaks them down into 3 templates: study guide, briefing doc and timeline. These templates are designed to help a student, associate or clerk quickly summarise, learn and understand the contents to be more productive. Study guide - a short quiz of questions and answered generated by the AI Agent using the contents of the document. Briefing Doc - key information and insights are extracted by the AI into a digestable form. Timeline - key events, durations and people are identified and listed into a simple to understand timeline by the AI How it works A local file trigger watches a local network directory for new documents. New documents are imported into the workflow, its contents extracted and vectorised into a Qdrant vector store to build a mini-knowledgebase. The document then passes through a series of template generating prompts where the AI will perform "research" on the knowledgebase to generate the template contents. Generated study guide, briefing and timeline documents are exported to a designated folder for the user. Requirements Self-hosted version of n8n. Qdrant instance for knowledgebase. Mistral.ai account for embeddings and AI model. Customising your workflow Try adding your own templates or adjusting the existing templates to suit your unique use-case. Anything is quite possible and limited only by your imagination! Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/1VV5R2nW-IhVcFP_k8uEks4LsLRZrHSNG/view?usp=sharing

This workflow gathers papers in Arxiv and specific arxiv category AI helps to make summarized form of newsletter and send it to subscriber using gmail Arxive paper trend newsletter Setup Supabase Table schema user_email: Text - Mandatory arxiv_cat: [Text] interested_papers: [Text] keyword: [Text] Example { "id": 8, "created_at": "2024-09-24T12:31:17.09491+00:00", "user_email": "test@test.com", "arxiv_cat": [ "cs.AI", "cs.LG,cs.AR" ], "interested_papers": null, "keyword": [ "AI architecture which includes long context problem" ] } Qdrant vector store default setup Setup for sub workflows Get arxiv category by AI for given keyword Get arxiv categories Get arxiv papers this week and scoring by AI Filter by keyword within given documents Extract paper information Write newsletter by AI

How It Works This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, the official n8n documentation—and then build a chatbot to ask it questions. Think of it like this: instead of a general-knowledge AI, you're building an expert librarian. 🔧 Workflow Overview The workflow is split into two main parts: Part 1: Indexing the Knowledge (📚 Building the Library) This is a one-time process you run manually. The workflow will: Automatically scrape all pages of the n8n documentation. Break them down into small, digestible chunks. Use an AI model to create a numerical representation (an embedding) for each chunk. Store these embeddings in n8n's built-in Simple Vector Store. > This is like a librarian reading every book and creating a hyper-detailed index card for every paragraph. > ⚠️ Important: This in-memory knowledge base is temporary. It will be erased if you restart your n8n instance. You'll need to run the indexing process again in that case. Part 2: The AI Agent (🧠 The Expert Librarian) This is the chat interface. When you ask a question: The AI agent doesn't guess the answer. It searches the knowledge base to find the most relevant “index cards” (chunks). It feeds those chunks to a language model (Gemini) with strict instructions: > “Answer the user's question using ONLY this information.” This ensures answers are accurate, factual, and grounded in your documents. 🚀 Setup Steps > Total setup time: ~2 minutes > Indexing time: ~15–20 minutes This template uses n8n’s built-in tools, so no external database is needed. 1. Configure OpenAI Credentials You’ll need an OpenAI API key (for GPT models). In your n8n workflow: Go to any of the three OpenAI nodes (e.g., OpenAI Chat Model). Click the Credential dropdown → + Create New Credential. Enter your OpenAI API key and save. 2. Apply Credentials to All Nodes Your new credential is now saved. Go to the other two OpenAI nodes (e.g., OpenAI Embeddings) and select the newly created credential from the dropdown. 3. Build the Knowledge Base Find the Start Indexing manual trigger node (top-left of the workflow). Click the Execute Workflow button to start indexing. > ⚠️ Be patient: This takes 15–20 minutes to scrape and process the full documentation. > You only need to do this once per n8n session. 4. Chat With Your Expert Agent After indexing completes, activate the entire workflow (toggle at the top). Open the RAG Chatbot chat trigger node (bottom-left). Copy its Public URL. Open it in a new tab and ask questions about n8n! Example questions: "How does the IF node work?" "What is a sub-workflow?" 👤 Credits All credits go to Lucas Peyrin 🔗 lucaspeyrin on n8n.io

Enhance Security Operations with the Venafi Slack CertBot! Venafi Presentation - Watch Video Our Venafi Slack CertBot is strategically designed to facilitate immediate security operations directly from Slack. This tool allows end users to request Certificate Signing Requests that are automatically approved or passed to the Secops team for manual approval depending on the Virustotal analysis of the requested domain. Not only does this help centralize requests, but it helps an organization maintain the security certifications by allowing automated processes to log and analyze requests in real time. Workflow Highlights: Interactive Modals**: Utilizes Slack modals to gather user inputs for scan configurations and report generation, providing a user-friendly interface for complex operations. Dynamic Workflow Execution**: Integrates seamlessly with Venafi to execute CSR generation and if any issues are found, AI can generate a custom report that is then passed to a slack teams channel for manual approval with the press of a single button. Operational Flow: Parse Webhook Data**: Captures and parses incoming data from Slack to understand user commands accurately. Execute Actions**: Depending on the user's selection, the workflow triggers other actions within the flow like automatic Virustotal Scanning. Respond to Slack**: Ensures that every interaction is acknowledged, maintaining a smooth user experience by managing modal popups and sending appropriate responses. Setup Instructions: Verify that Slack and Qualys API integrations are correctly configured for seamless interaction. Customize the modal interfaces to align with your organization's operational protocols and security policies. Test the workflow to ensure that it responds accurately to Slack commands and that the integration with Qualys is functioning as expected. Need Assistance? Explore Venafi's Documentation or get help from the n8n Community for more detailed guidance on setup and customization. Deploy this bot within your Slack environment to significantly enhance the efficiency and responsiveness of your security operations, enabling proactive management of CSR's.

The Ultimate Gmail Analysis and Visual Summarization Template This workflow showcases various useful Gmail search, filter, and AI categorization operations and generates a knowledge graph for your mail using the InfraNodus GraphRAG API, which you can use to reveal the main topics and blind spots in your correspondence. InfraNodus will then target those blind spots to generate interesting research questions for you and send the topical summary and insights via Telegram. You can also click the generated graph and explore the blind spots inside InfraNodus using the interactive visual interface: What is it useful for? Learn about advanced Gmail search, filtering, and AI categorization functions** that can be useful for your other workflows Analyze all your personal messages for the last week to get an overview of the main topics Analyze all your Sent messages to find recurrent topics and gaps and generate ideas based. on those gaps Generate ideas based on specific message filters (Personal, Promos, from a specific person, AI-defined criteria, e.g. urgency) Get an overview of an interaction with a specific person / company Get an overview of your notes Generate new ideas based on your correspondence on a certain topic (e.g. "business") Learn about various n8n nodes useful for email processing, filtering, and data conversion Never miss important topics, use AI filter to get notified of the urgent and important emails via Telegram How it works This template can be triggered in multiple ways: automatically in regular intervals (daily, weekly), manually in n8n, or via a private password-protected URL form where you can specify your search and filtering criteria When you start the workflow, you specify: your Gmail search filters (can be combined, e.g. after:2025/06/01 label:personal business to search for all emails received after 1 June 2025, filed in the Personal category containing the word "business". (optional, if empty, will retrieve all the emails or limited to the number you set in the Gmail node) Additional Gmail labels (e.g. SENT or CATEGORY_PERSONAL or your custom categories). Use the search filter for faster processing (e.g. prefer label:person to CATEGORY_PERSONAL, but labels can be useful for additional filtering for your search queries) (optional, if empty, will retrieve all the emails) AI filtering criteria** — set an additional classification criteria used to filter out the emails, e.g. "Only the urgent, personal emails" — in that case, AI classification node working with Google's Gemini AI will be activated and will only pass through the email based on the criteria you specify. Whether you want to build a text graph or a social graph — see the workflow for detailed explanation of each Use snippets of emails (default) or full text (for thorough analysis). We prefer snippets as it's faster and your graph context doesn't get biased towards longer emails this way. Once you set up your search parameters in Steps 1 and 2, the template will follow the following steps: Step 3 — retrieve Google emails that satisfy your filter criteria. Filter them by additional labels provided if applicable. Step 4 - if the user chooses to analyze full text, use additional Gmail node that retrieves the full text of the email message Step 5 — if AI filter rule is provided, use the AI Classifier node with Google Gemini Pro 2.5 model to classify the email based on the rule provided. Bypass if empty. Step 6 - format the text or the email snippets to add the sender meta-data and category and to prepare to submit to InfraNodus Step 7 - submit the data to the InfraNodus HTTP graphAndEntries endpoint and generate a knowledge graph Step 8 - access this graph via the graphAndAdvice endpoint) and generate a topical summary based on the GraphRAG representation and insight questions bridging the gaps identified. Send the results via a Telegram bot. We use Telegram, because it takes only 30 seconds to set up a bot with an API, unlike Discord or Slack, which is long and cumbersome to set up. You can also attach a Gmail send node and generate an email instead. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Add this Authorization code in Steps 7 and 8 of the workflow. Come up with the name of the graph and change it in the HTTP InfraNodus nodes in the steps 7 and 8 and also in the Telegram nodes that send a link to the graph. For additional settings you can use in the HTTP InfraNodus nodes, see the InfraNodus access points page. Authorize your Gmail account for Steps 2 and 3 Gmail nodes. The easiest way to set it up is to open a free Google Console API account and to create an OAuth access point for n8n. You can then reuse it with other Google services like Google Sheets, Drive, etc. So it's a useful thing to have in general. Set up the Gemini AI API key using the instructions in the Step 5 Gemini AI node. Set up the Telegram node bot for the Step 8. It takes only 30 seconds: just go to @botfather and type in /newbot and you'll have an API key ready. To get the conversation ID, follow the n8n / Telegram instructions in the node itself. Once everything is ready, try to run the default automated workflow to test if everything works well, then use the Form for playing around with specific filters that you may find useful. Requirements An InfraNodus account and API key An Google Cloud API OAuth client and key for Gmail access A Gemini AI API key A Telegram bot API key FAQ 1. What's the best search query to use? I personally like starting with analyzing the messages Gmail tags as "personal" from the last week (using the after:2025/05/28 label:personal search query) using the social graph settings. It helps me see who I interacted with, what it was about, and gives me a good bird's eye view into my last week's interactions, helping me see if I didn't miss anything. I also find it useful to analyze the sent messages (using the after:2025/05/28 label:sent search filter or SENT category filter) as it helps me see what I was writing about recently and understand some recurrent topics and gaps in my interactions. Finally, I also like to analyze notes (label:notes) or specific correspondence (from:your_friend@gmail.com) to get an overview and find gaps in the conversations. 2. Why use InfraNodus and not an AI summarization module? You probably get a lot of spam, so your AI will get overwhelmed with the content that's not really useful. The InfraNodus graph helps you see the important patterns and discover what's missing by focusing on the gaps. You can use the interactive graph to quickly remove the stuff you don't need and to focus on the most relevant topics and conversations. Customizing this workflow You can connect a Gmail node instead of the Telegram one if you prefer to receive notifications directly by email. I don't like using Slack and Discord because their bots are too difficult to set up and take too long. Check out the complete setup guide for this workflow at https://support.noduslabs.com/hc/en-us/articles/20394884531996-Build-a-Knowledge-Graph-and-Extract-Insights-from-Gmail-Emails-with-n8n-and-InfraNodus with a video tutorial coming soon and the links to other n8n workflows. Check our other n8n workflows at https://n8n.io/creators/infranodus/ for useful content gap analysis, expert panel, and marketing, and research workflows that utilize GraphRAG for better AI generation. Finally, check out https://infranodus.com to learn more about our network analysis technology used to build knowledge graphs from text.

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.

Extract Facebook Group Posts with Airtop Use Case Extracting content from Facebook Groups allows community managers, marketers, and researchers to gather insights, monitor discussions, and collect engagement metrics efficiently. This automation streamlines the process of retrieving non-sponsored post data from group feeds. What This Automation Does This automation extracts key post details from a Facebook Group feed using the following input parameters: Facebook Group URL**: The URL of the Facebook Group feed you want to scrape. Airtop Profile**: The name of your Airtop Profile authenticated to Facebook. It returns up to 5 non-sponsored posts with the following attributes for each: Post text Post URL Page/profile URL Timestamp Number of likes Number of shares Number of comments Page or profile details Post thumbnail How It Works Form Trigger: Collects the Facebook Group URL and Airtop Profile via a form. Browser Automation: Initiates a new browser session using Airtop. Navigates to the provided Facebook Group feed. Uses an AI prompt to extract post data, including interaction metrics and profile information. Structured Output: The results are returned in a defined JSON schema, ready for downstream use. Setup Requirements Airtop API Key — Free to generate. An Airtop Profile logged into Facebook. Next Steps Integrate With Analytics Tools**: Feed the output into dashboards or analytics platforms to monitor community engagement. Automate Alerts**: Trigger notifications for posts matching certain criteria (e.g., high engagement, keywords). Combine With Comment Automation**: Extend this to reply to posts or engage with users using other Airtop automations. Let me know if you’d like this saved as a .md file or included in your Airtop automation library. Read more about how to extract posts from Facebook groups

Complete MCP server exposing all LinkedIn Tool operations to AI agents. Zero configuration needed - all 1 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 LinkedIn Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n LinkedIn Tool tool with full error handling 📋 Available Operations (1 total) Every possible LinkedIn Tool operation is included: 🔧 Post (1 operations) • Create a post 🤖 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 LinkedIn 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 LinkedIn 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.

Complete MCP server exposing all Google Translate Tool operations to AI agents. Zero configuration needed - all 1 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 Google Translate Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Google Translate Tool tool with full error handling 📋 Available Operations (1 total) Every possible Google Translate Tool operation is included: 🔧 Language (1 operations) • Translate a language 🤖 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 Google Translate 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 Google Translate 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.

🛠️ Google Cloud Natural Language Tool MCP Server Complete MCP server exposing all Google Cloud Natural Language Tool operations to AI agents. Zero configuration needed - all 1 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 Google Cloud Natural Language Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Google Cloud Natural Language Tool tool with full error handling 📋 Available Operations (1 total) Every possible Google Cloud Natural Language Tool operation is included: 🔧 Document (1 operations) • Analyze sentiment 🤖 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 Google Cloud Natural Language 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 Google Cloud Natural Language 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.

🛠️ Dropcontact Tool MCP Server Complete MCP server exposing all Dropcontact Tool operations to AI agents. Zero configuration needed - all 2 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 Dropcontact Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Dropcontact Tool tool with full error handling 📋 Available Operations (2 total) Every possible Dropcontact Tool operation is included: 📇 Contact (2 operations) • Find B2B emails • Fetch Request Contact 🤖 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 Dropcontact 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 Dropcontact 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.

🛠️ DHL Tool MCP Server Complete MCP server exposing all DHL Tool operations to AI agents. Zero configuration needed - all 1 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 DHL Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n DHL Tool tool with full error handling 📋 Available Operations (1 total) Every possible DHL Tool operation is included: 🔧 Shipment (1 operations) • Get tracking details for a shipment 🤖 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 DHL 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 DHL 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.