Workflow Templates

The provided workflow in n8n is designed to create a Business WhatsApp AI RAG (Retrieval-Augmented Generation) Chatbot. How it works: Webhook Setup: The workflow begins by setting up webhooks for verification and response. The Verify webhook receives GET requests and sends back a verification code, while the Respond webhook handles incoming POST requests from Meta regarding WhatsApp messages. Message Handling: Once a message is received, the workflow checks if the incoming JSON contains a user message. If it does, the message is processed further; otherwise, a generic response is sent. AI Agent Interaction: The user's message is passed to the AI Agent node, which uses a conversational agent with a predefined system message tailored for an electronics store. This ensures that the AI provides accurate and professional responses based on the knowledge base. Knowledge Base Utilization: The AI Agent references a knowledge base stored in Qdrant, a vector database. Documents from Google Drive are downloaded, vectorized using OpenAI embeddings, and stored in Qdrant for retrieval during conversations. Response Generation: The AI Agent generates a response using the OpenAI chat model (gpt-4o-mini) and sends it back to the user via WhatsApp. Set up steps: Create Qdrant Collection: Update the QDRANTURL and COLLECTION variables in the workflow. Use the Create collection HTTP request node to initialize the collection in Qdrant. Vectorize Documents: Configure the Get folder and Download Files nodes to fetch documents from a specified Google Drive folder. Use the Embeddings OpenAI node to generate embeddings for the downloaded files. Store the vectorized documents in Qdrant using the Qdrant Vector Store node. Configure Webhooks: Ensure both Verify and Respond webhooks have the same URL. Set the Verify webhook to use the GET HTTP method and the Respond webhook to use the POST HTTP method. Set Up AI Agent: Define the system prompt for the AI Agent, specifying guidelines for product information, technical support, customer service, and knowledge base usage. Link the AI Agent to the OpenAI chat model and configure any additional tools as needed. Test Workflow: Trigger the workflow manually using the When clicking ‘Test workflow’ node to ensure all components are functioning correctly. Monitor the flow of data through the nodes and verify that responses are being generated and sent accurately. By following these steps, the workflow will be fully operational, enabling a robust AI-powered chatbot capable of handling customer inquiries via WhatsApp. Need help customizing? Contact me for consulting and support or add me on Linkedin.

🤖AI & Machine Learning

advanced

11 nodes35120 views

Bitrix24 AI-Powered RAG Chatbot for Open Line Channels

by Ferenc Erb

Overview Transform your Bitrix24 Open Line channels with an intelligent chatbot that leverages Retrieval-Augmented Generation (RAG) technology to provide accurate, document-based responses to customer inquiries in real-time. Use Case This workflow is designed for organizations that want to enhance their customer support capabilities in Bitrix24 by providing automated, knowledge-based responses to customer inquiries. It's particularly useful for: Customer service teams handling repetitive questions Support departments with extensive documentation Sales teams needing quick access to product information Organizations looking to provide 24/7 customer support What This Workflow Does Smart Document Processing Automatically processes uploaded PDF documents Splits documents into manageable chunks Generates vector embeddings for semantic understanding Indexes content for efficient retrieval AI-Powered Responses Utilizes Google Gemini AI to generate natural language responses Constructs answers based on relevant document content Maintains conversation context for coherent interactions Provides fallback responses when information is not available Vector Database Integration Stores document embeddings in Qdrant vector database Enables semantic search beyond simple keyword matching Retrieves the most relevant information for each query Maintains a persistent knowledge base that grows over time Webhook Handler Processes incoming messages from Bitrix24 Open Line channels Handles authentication and security validation Routes different types of events to appropriate handlers Manages session and conversation state Event Routing Intelligently routes different event types: ONIMBOTMESSAGEADD: Processes new user messages ONIMBOTJOINCHAT: Handles bot joining a conversation ONAPPINSTALL: Manages application installation ONIMBOTDELETE: Handles bot deletion Document Management Organizes processed documents in designated folders Tracks document processing status Moves indexed documents to appropriate locations Maintains document metadata for reference Interactive Menu Provides menu-based options for common user requests Customizable menu items and responses Easy navigation for users seeking specific information Fallback to operator option when needed Technical Architecture Components Webhook Handler: Receives and validates incoming requests from Bitrix24 Credential Manager: Securely manages authentication tokens and API keys Event Router: Directs events to appropriate processing functions Document Processor: Handles document loading, chunking, and embedding Vector Store: Qdrant database for storing and retrieving document embeddings Retrieval System: Searches for relevant document chunks based on user queries LLM Integration: Google Gemini model for generating natural language responses Response Manager: Formats and sends responses back to Bitrix24 Integration Points Bitrix24 API**: For bot registration, message handling, and user interaction Ollama API**: For generating document embeddings Qdrant API**: For vector storage and retrieval Google Gemini API**: For AI-powered response generation Setup Instructions Prerequisites Active Bitrix24 account with Open Line channels enabled Access to n8n workflow system Ollama API credentials Qdrant vector database access Google Gemini API key Configuration Steps Initial Setup Import the workflow into your n8n instance Configure credentials for all services Set up webhook endpoints Bitrix24 Configuration Create a new Bitrix24 application Configure webhook URLs Set appropriate permissions Install the application to your Bitrix24 account Document Storage Create a designated folder in Bitrix24 for knowledge base documents Configure folder paths in the workflow settings Upload initial documents to be processed Bot Configuration Customize bot name, avatar, and description Configure welcome messages and menu options Set up fallback responses Testing Verify successful installation Test document processing pipeline Send test queries to evaluate response qu

AI content creation and auto WordPress publishing with Pexels API image workflow

by Mateusz Kosiorek

AI powered content creation and WordPress publishing workflow Summary This workflow automates the entire process of blog content creation, from idea generation and article writing using Google Gemini, to sourcing images from Pexels and publishing directly to your WordPress site. It uses Google Sheets as a central hub for managing content ideas and tracking their status, all orchestrated through interactive n8n forms. Key features AI driven content:** Leverages Google Gemini for generating: Full blog articles based on prompts. Relevant keywords for image searching. New blog topic ideas. Automated image sourcing:** Searches Pexels for suitable images based on AI generated keywords and downloads them. WordPress integration:** Creates new posts with AI generated title and content. Uploads sourced images to the WordPress media library. Sets the uploaded image as the featured image for the post. Google Sheets management:** Fetches content ideas (prompts) marked as "not generated". Updates the sheet after a post is generated with the post ID, title, and generation date. Adds newly AI generated blog topic ideas to the sheet. Interactive forms:** Main trigger form to choose between generating content or adding new ideas. Forms to input topics for idea generation. Confirmation forms at the end of processes. Structured output parsing:** Ensures AI responses for topic generation are correctly formatted as JSON. How it works The workflow is initiated via an n8n Form Trigger: Select Action, allowing the user to choose one of two main paths: 1. Generate content path: Fetch idea: The Fetch unprocessed ideas (Google Sheets) node retrieves a row from your sheet where the "Generated" column is "no". Set prompt: The Set prompt node prepares the topic from the sheet for the AI. Generate article: The Generate article AI (Langchain Agent with Google Gemini) node takes the prompt and writes a full article. Generate image keyword: The Generate image keyword AI (Langchain Agent with Google Gemini) node creates a concise search term based on the article topic. Search image: The Search Pexels image (HTTP Request) node uses the generated keyword to find a relevant image via the Pexels API. Create WordPress post: The Create WordPress post node publishes the AI generated article and initial image metadata to your WordPress site. Download and upload image: The Download Pexels image (HTTP Request) node fetches the actual image file, and the Upload image (HTTP Request) node uploads it to your WordPress media library. Set featured image: The Set featured image (HTTP Request) node links the uploaded image as the featured image for the newly created post. Update sheet: The Update Google Sheet node marks the idea as "yes" in your Google Sheet and adds the WordPress post ID and title. Confirmation: A Form: End post generation node displays a completion message. 2. Add ideas path: Input topic: The Form: Enter topic for ideas node prompts the user to enter a general subject. Generate topics: The Generate blog topics AI (Langchain Agent with Google Gemini and Structured Output Parser) node generates five SEO friendly blog topic ideas based on the user's input, formatted as JSON. Process topics: The Split topics node separates the generated list of topics into individual items. Add to sheet: For each topic, the Add ideas to sheet (Google Sheets) node appends it as a new row, marked with "Generated: no". Loop or end: The Form: Add more topics? node asks the user if they want to generate more ideas or end the process. If "NEXT", it loops back to the Form: Enter topic for ideas. If "END", a Form: End idea generation node displays a completion message with the list of added topics. Nodes used Form Trigger If Google Sheets Set Langchain Agent (with Google Gemini Chat Model) Structured Output Parser (Langchain) HTTP Request (for Pexels API and WordPress Media/Post updates) WordPress Split Out Form (for user interaction and completion messages) Sticky Note (for instructions within the workflow) Setup instructions Credentials: Google Sheets: Configure your Google Sheets OAuth2 credentials in the Fetch unprocessed ideas, Update Google Sheet, and Add ideas to sheet nodes. WordPress: Configure your WordPress API credentials in the Create WordPress post, Upload image, and Set featured image nodes. Google Gemini: Configure your Google Gemini (PaLM) API key in the Gemini model for article, Gemini model for image keyword, and Gemini model for topics nodes. API keys and URLs: Pexels: In the Search Pexels image node, replace <YOUR_PEXELS_API_KEY> in the Authorization header with your actual Pexels API key. WordPress URL: In the Upload image and Set featured image nodes, replace <YOUR_WORDPRESS_URL> in the URL field with your WordPress site's domain (e.g., yourblog.com). Google Sheet configuration: Ensure your Google Sheet (specified by Document ID in Google Sheets nodes) has a sheet named Sheet1 (or update the Sheet Name parameter). The sheet should have at least the following columns: Prompt (for the blog idea/topic), Generated (to track status, e.g., "no" or "yes"), row_number (automatically populated by n8n when reading), Date, Title (for the final WordPress post title), Post ID. Activate the workflow. The Form Trigger: Select Action will provide a webhook URL to initiate the process. Customization ideas Modify the AI prompts in the Langchain Agent nodes for different tones, styles, or content structures. Change the Google Gemini models used for different cost/performance balances. Integrate other image sources instead of or in addition to Pexels. Add steps for social media sharing after a post is published. Extend the Google Sheet to track more metrics like word count or target keywords. Implement more sophisticated error handling. Use cases Automating blog content generation for personal or company blogs. Streamlining content marketing efforts. Quickly populating new websites with initial content. Assisting SEO agencies in creating draft content for clients. Helping solo bloggers maintain a consistent publishing schedule.

Automate Course Registration Leads from Facebook Ads to KlickTipp

by KlickTipp

Community Node Disclaimer: This workflow uses KlickTipp community nodes. How It Works: Facebook Lead Ads to KlickTipp Integration: This workflow automatically transfers lead information submitted via Facebook Lead Ads into KlickTipp. It is ideal for automating course registrations or similar campaigns, enabling targeted email sequences based on user input. Data Handling: Lead data from Facebook is received via webhook, matched to KlickTipp’s custom fields, and the contact is tagged for segmentation and automation. Key Features Webhook Trigger for Facebook Lead Ads: Captures new lead form submissions from Facebook, including: Name Email address Chosen course Preferred payment method Optional comments Data Mapping & Validation: Maps Facebook field values to pre-defined custom fields in KlickTipp Subscriber Management in KlickTipp: Adds or updates leads as subscribers in KlickTipp Includes mapping to custom fields such as: Facebook_Leads_Ads_Kursauswahl Facebook_Leads_Ads_Zahlungsweise Facebook_Leads_Ads_Kommentar Assigns relevant tags for automated campaign triggers Setup Instructions 1. Prepare KlickTipp Custom Fields: Before using the workflow, create the following custom fields in KlickTipp under → Contacts → Custom fields: | Name | Datentyp | | - | - | | Facebook_Leads_Ads_Kommentar | Zeile | | Facebook_Leads_Ads_Kursauswahl | Zeile | | Facebook_Leads_Ads_Zahlungsweise | Zeile | 2. Facebook Lead Ads Setup: Create a lead form under Facebook Ads Manager Include custom fields for course interest, payment preference, and comments 3. Set Up Facebook Webhook in n8n: Use the Facebook Lead Ads node to create a webhook Authenticate your Facebook account Choose the Page and corresponding lead form Save and activate the webhook 4. Map Data to KlickTipp Fields: Open the KlickTipp node to Authenticate with your credentials (username&password) Map the fields from the Facebook webhook to the according custom fields in KlickTipp. Testing & Deployment Run a Test: Use Meta’s testing tool to generate a test lead Run the n8n workflow once manually Note: Facebook test email (e.g., test@fb.com) is invalid—expect an error in KlickTipp during testing. You can pin the output of the node and manipulate the address to a valid test-address. Workflow Logic Webhook Trigger from Facebook: Initiates workflow upon new lead form submission Add or Update Contact in KlickTipp: Submits mapped data into your KlickTipp account Benefits Automated Lead Management: No manual data transfers needed—new Facebook leads are instantly pushed to KlickTipp. Personalized Campaigns: Segment leads based on selected course or payment method for targeted follow-up emails. Notes: Customization: Adjust field mappings in the KlickTipp node based on your lead form structure. Ensure all required fields (email, opt-in, etc.) are mapped correctly. Resources: Use the Meta Lead Ads Testing Tool to simulate lead submissions during setup. Look into our knowledgebase article Send Facebook Leads to KlickTipp with Make or n8n to learn more. Use KlickTipp Community Node in n8n Automate Workflows: KlickTipp Integration in n8n

beginner

0 nodes1820 views

Generate Content Strategy Reports Analyzing Reddit, YouTube & X with Gemini

by Sheryl

Description This workflow provides a powerful AI assistant for content creators, book editors, and marketers. It automates the collection and analysis of trending discussions from Reddit, YouTube, and X (Twitter), generating insightful topic reports. This frees you from hours of tedious data compilation, allowing you to make faster, more accurate topic decisions based on deep AI analysis. How it works This workflow simulates the complete research process of a strategic editor: Initiate & Collect: A user submits a keyword via a public Form Trigger. The workflow then automatically fetches relevant, trending content in parallel from the official APIs of Reddit, YouTube, and X (Twitter). Multi-stage AI Processing & Analysis: The workflow utilizes a layered AI pipeline to process the data. First, a lightweight Gemini model in the AI Pre-filter Content node rapidly screens the vast amount of content to filter out noise. Next, a more powerful Gemini Pro model in the AI Deep Analysis node performs a detailed, structured analysis on each high-value item, extracting summaries, sentiment, and key arguments. Finally, a "strategist" AI model in the AI Synthesize Final Report node aggregates all analyses to generate the comprehensive final topic report in HTML. Multi-Channel Report Distribution: The workflow distributes the final report to multiple channels based on pre-defined templates. The Send Gmail Report node sends the complete HTML report. The Send Feishu Notification node sends a concise summary card to a group chat. Meanwhile, the Archive to Google Sheets node archives key data. Setup Steps This workflow takes approximately 20-30 minutes to set up, with most of the time spent connecting your accounts. Connect Your API Accounts: In the n8n Credentials section, you will need to prepare and connect credentials for the following services: Google: For the Gemini AI model, Gmail sending, and Google Sheets archiving. This requires a Google Cloud API Key and OAuth2 credentials. Reddit: For fetching Reddit posts. This requires a Reddit account with OAuth2 configured in n8n to allow searches. YouTube: For collecting YouTube videos. You'll need to enable the YouTube Data API v3 in your Google Cloud Console and get an API Key. Twitter: For the official Twitter node, requiring a free developer account and an App with v2 API access. Configure Output Channels: In the final nodes (Send Gmail Report, Send Feishu Notification, Archive to Google Sheets), update the recipient email address, the Feishu bot's Webhook URL, and the target spreadsheet ID to match your own. Activate and Share the Trigger: Activate the workflow. The first Form Trigger node will automatically generate a public URL. Share this link with your team members to let them start using the tool.

intermediate

9 nodes480 views

Automate Blog-to-Social Media with GPT-4 for LinkedIn, X, and Reddit

by Le Nguyen

Turn your blog into a set-and-forget content engine: every new article is instantly repurposed into channel-specific social posts with visuals, keeping your brand visible on LinkedIn, X, and Reddit without extra copywriting time. Perfect for lean marketing teams who want consistent, always-on distribution from a single source of content. How it works • Watches your blog RSS feed (or receives a single URL) and detects new articles. • Saves each post in Postgres so every article is only processed once. • Fetches the article HTML, extracts the main body content and sends it to OpenAI (GPT-4.1). • OpenAI creates platform-optimized copy: 1 LinkedIn post, 1 X/Twitter post, 1 Reddit post + image prompts. • Generates on-brand images with OpenAI and publishes everything automatically to LinkedIn, X, and Reddit. • You can also trigger it manually or via webhook whenever you want to push a specific campaign. Setup Steps • Time: around 20–40 minutes for someone familiar with n8n and the platforms. • Create a Postgres table “rss_items” with fields: guid (PRIMARY KEY), title, link, published_at. • Add credentials in n8n for: – Postgres – OpenAI – LinkedIn OAuth2 – X/Twitter OAuth2 + OAuth1 (for media upload) – Reddit OAuth2 • In the RSS node, set your blog feed URL (for example: https://yourblog.com/feed). • In the webhook node, confirm the URL/path you want external tools or other workflows to call with a “link” field. • Run the manual trigger with one test blog URL to verify: – Article content is extracted correctly. – AI returns LinkedIn/X/Reddit posts and image prompts. – Posts and images appear correctly on all social accounts. • Once tests look good, enable the Schedule Trigger so Blog2Social AI runs automatically at your chosen interval.

intermediate

7 nodes28 views

Gmail MCP Workflow - AI-Powered Email Management

by David Olusola

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. MCP Gmail Workflow – AI-Powered Email Management ✨ What It Does A smart n8n workflow that connects Gmail with an AI agent (via MCP), letting you send, read, and organize emails using natural language. ⚙️ Key Features 🧠 AI Commands: “Send email to John about the budget” 📥 Inbox Control: Mark read/unread, apply/remove labels 🗂 Smart Organization: Auto-label based on content 🤖 MCP-Ready: Works with Claude, ChatGPT, etc. 🎯 Use Cases “📤 Send a follow-up to the client about yesterday’s meeting” “📬 Mark all newsletters as read and label ‘Newsletter’” “🧾 Summarize latest email from Sarah” “🗃 Label all Project X emails as ‘Project-X-2024’” “⭐ Find unread emails from my manager and mark as important” 🛠 Setup Guide 🔑 Prerequisites n8n (self-hosted or cloud) Gmail API credentials MCP-compatible AI (optional but powerful) 📥 1. Import Workflow Copy JSON → Open n8n → Import → Paste → Done ✅ 🔐 2. Gmail OAuth2 Setup Create Google project → Enable Gmail API Create OAuth2 creds → Add n8n redirect URI In n8n: Add Gmail OAuth2 → Paste Client ID/Secret → Connect 🧩 3. Update Credential References Find your credential ID in n8n Update each Gmail node with your ID 🧠 4. MCP Trigger (Optional) Use provided webhook URL in your AI system Send test prompts to verify connection 🧪 5. Test Key Actions ✅ “Send a test email” ✅ “Read latest email” ✅ “Label last email as ‘Test’” ✅ “Mark latest email as unread” ⚙️ 6. Advanced Tips Create custom labels in Gmail Use HTTPS + webhook auth Add retries and error handling in n8n 🧯 Troubleshooting ❗ Gmail Auth Error? → Re-auth and check redirect URI ❗ Webhook not firing? → Check endpoint + manual test ❗ Label errors? → Use correct label names or IDs ✅ Required Gmail Scopes: gmail.modify gmail.send 📈 Best Practices 🔁 Test regularly 🔒 Use minimal permissions 🏷 Consistent label naming 🔍 Monitor execution + webhook logs 🎉 You’re All Set! Control Gmail with your voice or text through AI. Make managing emails smarter, faster, and 100% automated 💌

beginner

0 nodes124 views

Generate & Enrich LinkedIn Leads with Apollo.io, LinkedIn API, Mail.so & GPT-3.5

by Joseph

Note: Now includes an Apify alternative for Rapid API (Some users can't create new accounts on Rapid API, so I have added an alternative for you. But immediately you are able to get access to Rapid API, please use that option, it returns more detailed data). *Scroll to bottom for APify setup guide* This n8n workflow automates LinkedIn lead generation, enrichment, and activity analysis using Apollo.io, RapidAPI, Google Sheets and Mail.so. Perfect for sales teams, founders, B2B marketers, and cold outreach pros who want personalized lead insights to drive better conversion rates. ⚙️ How This Workflow Works The workflow is broken down into several key steps, each designed to help you build and enrich a valuable list of LinkedIn leads: 1. 🔑 Lead Discovery (Keyword Search via Apollo) Pulls leads using Apollo.io's API based on keywords, industries, or job titles. Saves lead name, title, company, and LinkedIn URL to your Google Sheet. You can replace the trigger node from the form node to a webhook, whatsapp, telegram, etc, any way for you to send over your query variables over to initiate the workflow. 2. 🧠 Username Extraction (from LinkedIn URL) Extracts the LinkedIn username from profile URLs using a simple script node. This is required for further enrichment via RapidAPI. 3. ✉️ Email Lookup (via Apollo User ID) Uses the Apollo User ID to retrieve the lead’s verified work email. Ensures high-quality leads with reliable contact info. To double check that the email is currently valid, we use the mail.so api and filter out emails that fail deliverability and mx-record check. We don't wanna risk sending emails to no longer existent addresses, right? 4. 🧾 Profile Summary Enrichment (via RapidAPI) Queries the LinkedIn Data API to fetch a lead’s profile summary/bio. Gives you a deeper understanding of their background and expertise. 5. 📰 Recent Activity Collection (Posts & Reposts) Retrieves recent posts or reposts from each lead’s profile. Great for tailoring outreach with reference to what they’re currently talking about. 6. 🗂️ Leads Database Update All enriched data is written to the same Google Sheet. New columns are filled in without overwriting existing data. ✅ Smart Retry & Row Status Logic Every subworkflow includes a fail-safe mechanism to ensure: ✅ Each row has status columns (e.g., done, failed, pending). 🕒 A scheduled retry workflow resets failed rows to pending after 2 weeks (customizable). 💬 This gives failed enrichments another chance to be processed later, reducing data loss. 📋 Google Sheets Setup Template 1: Apollo Leads Scraping & Enrichment Template 2: Enriched Leads Database Make a copy to your Drive and use. Columns will be filled as each subworkflow runs (email, summary, interests, etc.) 🔐 Required API Keys To use this workflow, you’ll need the following credentials: 🧩 Apollo.io Sign up and get your key here: Apollo.io API Keys ⚠️ Important: Toggle the “Master API Key” option to ON when generating your key. This ensures the same key can be used for all Apollo endpoints in this workflow. 🌐 RapidAPI (LinkedIn Data API) Subscribe to the API here: LinkedIn Data API on RapidAPI Use the key in the x-rapidapi-key header in the relevant nodes. ✉️ Mail.so Sign up and get your key here: Mail.so API > 💡 For both APIs, set up the credentials in n8n as “Generic Credential” types. This way, you won’t need to reconfigure the headers in each node. 🛠️ Customization Options Modify the Apollo filters (location, industry, seniority) to target your ideal customers. Change retry interval in the scheduler (e.g., weekly instead of 2 weeks). Connect the database to your email campaign tool like Mailchimp or Instantly.ai. Replace the AI nodes with your desired AI agents and customize the system messages further to get desired results. 🆕 Apify Update Guide To use this workflow, you’ll need the following credentials: Login to Apify, then open this link; https://console.apify.com/actors/2SyF0bVxmgGr8IVCZ/ Click on integrations and scroll down to API Solutions and select "Use API endpoints". Scroll to "Run Actor synchronously and get dataset items" and copy the actor endpoint url then paste it in the placeholder inside the http node of Apify alternative flow "apify-actor-endpoint". That's it, you are set to go. I am available for custom n8n workflows, if you like my work, please get in touch with me on email at joseph@uppfy.com

Analyze Email Headers for IP Reputation and Spoofing Detection - Gmail

by Angel Menendez

Analyze Emails for Security Insights Who is this for? This workflow is ideal for IT professionals, security analysts, and organizations looking to enhance their email security practices. It is particularly useful for those who need to analyze Gmail email headers for IP tracking, spoofing detection, and sender reputation assessment. What problem is this workflow solving? Email spoofing and phishing attacks are significant cybersecurity threats. By analyzing email headers, this workflow provides detailed insights into the email's origin, authentication status, and the reputation of the sending IP address. It helps detect potential spoofing attempts and assess the trustworthiness of incoming emails. What this workflow does This n8n workflow automates the process of analyzing email headers received in Gmail. It performs the following key functions: Triggering and Email Header Extraction: It monitors Gmail inboxes for new emails and extracts their headers for analysis. Authentication Analysis: It validates SPF, DKIM, and DMARC authentication results to ensure the email adheres to industry-standard security protocols. IP Analysis: The workflow extracts the originating IP address and evaluates its reputation and geographic details using external APIs. Reputation Scoring: It integrates with IP Quality Score to detect spam activity and assess the sender's reputation. Consolidation and Webhook Response: All results are aggregated into a single JSON response, making it easy to integrate with third-party platforms or tools for further automation. Setup Authenticate Gmail: Configure the Gmail Trigger node with your Gmail account credentials. API Keys (Optional): Obtain an API key for IP Quality Score (https://ipqualityscore.com). Ensure the IP-API endpoint is accessible. This step is optional as ipqualityscore.com will provide a limited number of free lookups each month. See more details here. Activate the Workflow: Ensure the workflow is active to process incoming emails in real-time. How to customize this workflow to your needs Add Alerts:** Use the Gmail - Respond to Webhook node to trigger notifications in Slack, email, or any other communication channel. Integrate with SIEM:** Forward the workflow output to SIEM tools like Splunk or ELK Stack for further analysis. Modify Validation Rules:** Update SPF, DKIM, or DMARC logic in the Set nodes to align with your organization’s security policies. Expand IP Analysis:** Add more APIs or services to enrich IP reputation data, such as VirusTotal or AbuseIPDB. This workflow provides a robust foundation for email security monitoring and can be tailored to fit your organization's unique requirements. With its modular design and integration options, it’s a versatile tool to enhance your cybersecurity operations.

beginner

2 nodes5701 views

Conversational Kubernetes Management with GPT-4o and MCP Integration

by Reza Gholizade

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. Conversational Kubernetes Management with GPT-4o and MCP Integration This workflow enables you to manage Kubernetes clusters conversationally using OpenAI’s GPT-4o and a secure MCP (Model Context Protocol) server. It transforms natural language queries into actionable Kubernetes commands via a lightweight MCP API gateway — perfect for developers and platform engineers seeking to simplify cluster interaction. 🚀 Setup Instructions Import the Workflow Upload this template to your n8n instance. Configure Required Credentials OpenAI API Key: Add your GPT-4o API key in the credentials. MCP Client Node: Set the URL and auth for your MCP server. Test Kubernetes Access Ensure your MCP server is correctly configured and has access to the target Kubernetes cluster. 🧩 Prerequisites n8n version 0.240.0 or later Access to GPT-4o via OpenAI A running MCP server Kubernetes cluster credentials configured in your MCP backend ⚠️ Community Nodes Disclaimer This workflow uses custom community nodes (e.g., MCP Client). Make sure to review and trust these nodes before running in production. 🛠️ How It Works A webhook or chat input triggers the conversation. GPT-4o interprets the message and generates structured Kubernetes queries. MCP Client securely sends requests to your cluster. The result is returned and formatted for easy reading. 🔧 Customization Tips Tweak the GPT-4o prompt to match your tone or technical level. Extend MCP endpoints to support new Kubernetes actions. Add alerting or monitoring integrations (e.g., Slack, Prometheus). 🖼️ Template Screenshot 🧠 Example Prompts Show me all pods in the default namespace. Get logs for nginx pod in kube-system. List all deployments in staging. 📎 Additional Resources MCP Server on GitHub OpenAI Documentation n8n Docs Build smarter Kubernetes workflows with the power of AI !

🤖AI & Machine Learning

intermediate

4 nodes1643 views

AWS Cost & Usage Report Management for AI Agents

by David Ashby