Workflow Templates

Complete MCP server exposing all Humantic AI Tool operations to AI agents. Zero configuration needed - all 3 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 Humantic AI Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Humantic AI Tool tool with full error handling 📋 Available Operations (3 total) Every possible Humantic AI Tool operation is included: 🔧 Profile (3 operations) • Create a profile • Get a profile • Update a profile 🤖 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 Humantic AI 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 Humantic AI 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.

A reusable and production-ready n8n workflow that secures public webhooks using Bearer Token authentication and dynamic request validation. ✨ What It Does Verifies Bearer Token** Compares the Authorization header with a configured secret token. Validates Required Fields** Checks that all expected fields are present in the incoming request body. Returns Standardized JSON Responses** 401 Unauthorized if token is missing or invalid 400 Bad Request if required fields are missing 200 OK with a custom success payload 👤 Who It’s For Developers exposing n8n workflows as APIs No-code/low-code builders integrating with external forms or tools Anyone needing simple authentication and validation on incoming webhooks 💡 Why Use It 🔒 Secure: Prevents unauthorized access to your public workflows 🧼 Clean: Centralized configuration for token and required fields ⚙️ Flexible: Easy to extend and customize for any use case 🛠 Setup Instructions Configure Values in the Configuration Node Set your secret token: config.bearerToken = YOUR_TOKEN Define required request fields by key: Example: config.requiredFields.message = true; config.requiredFields.email = true; ✅ Only the keys matter – values can be anything. Plug in Your Business Logic Replace the "Add workflow nodes here" with your own logic. Customize the Success Response Edit the Create Response node to shape your success payload. 🧪 Use Cases Securing public form submissions Creating internal API endpoints Validating data from external services 📌 Use this as a base for building secure, API-style workflows in n8n. 👋 Hello! I'm Audun / xqus If my n8n workflows saved you time or sparked ideas, consider sending a little support my way. It helps me keep building cool stuff — and maybe grab a coffee ☕ along the way!

How it works: Webhook URL that responds to Requests with an AI generated Image based on the prompt provided in the URL. Setup Steps: Ideate your prompt URL Encode The Prompt (as shown in the Template) Authenticate with your OpenAI Credentials Put together the Webhook URL with your prompt and enter into a webbrowser In this way you can expose a public url to users, employee's etc. without exposing your OpenAI API Key to them. Click here to find a blog post with additional information.

This workflow processes emails received in Gmail and saves detailed information about each email to a MySQL database. Before using, you need to have: Gmail credentials MySQL database credentials A table in your database with the following columns: messageId (Gmail message ID) threadId snippet sender_name (nullable) sender_email recipient_name (nullable) recipient_email subject (nullable) How it works: The Gmail Trigger listens for new emails (checked every minute). A Code Node extracts the following fields from each email: Sender's name and email Recipient's name and email The MySQL Node inserts the extracted data into your database. If an entry with the same sender email already exists, it updates the record with the new details. How to use: Make sure your database table has all required columns listed above. Select the appropriate table and configure the matching column (e.g., id) to avoid duplicates. Customizing this Workflow: You can further modify the workflow to store attachments, timestamps, labels, or any other Gmail metadata as needed.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works? This workflow is an intelligent SEO analysis pipeline that ethically scrapes blog content and performs comprehensive SEO evaluation using AI. It receives blog URLs via webhook, validates permissions through robots.txt compliance, extracts content, and generates detailed SEO insights across four strategic dimensions: Content Optimization, Keyword Strategy, Technical SEO, and Backlink Building potential. The system prioritizes ethical web scraping by checking robots.txt permissions before proceeding, ensuring compliance with website policies. Upon successful analysis, it returns a structured JSON report with actionable SEO recommendations, performance scores, and optimization strategies. Technical Specifications Trigger: HTTP POST webhook Processing Time: 30-60 seconds depending on content size AI Model: GPT-4.1 minimum with specialized SEO analysis prompt. Output Format: Structured JSON Error Handling: Graceful failure with informative messages Compliance: Respects website robots.txt policies

Search LinkedIn companies and add them to Airtable CRM Who is this for? This template is ideal for sales teams, business development professionals, and marketers looking to build a robust prospect database without manual LinkedIn research. Perfect for agencies, consultants, and B2B companies targeting specific business profiles. What problem does this workflow solve? Manually researching companies on LinkedIn and adding them to your CRM is time-consuming and error-prone. This automation eliminates the tedious process of finding, qualifying, and importing prospects into your database. What this workflow does This workflow automatically searches for companies on LinkedIn based on your criteria (keywords, size, location), retrieves detailed information about each company, filters them based on quality indicators (follower count and website availability), and adds new companies to your Airtable CRM while preventing duplicates. Setup Create a Ghost Genius API account and get your API key Configure HTTP Request nodes with Header Auth credentials (Name: "Authorization", Value: "Bearer your_api_key") Create an Airtable base named "CRM" with columns: name, website, LinkedIn, id, etc. Set up your Airtable credentials following n8n documentation Add your company search selection criteria to the “Set Variables” node. How to customize this workflow Modify search parameters in the "Set Variables" node to target different industries, locations, or company sizes Adjust the follower count threshold in the "Filter Valid Companies" node based on your qualification criteria Customize the Airtable fields mapping in the "Add Company to CRM" node to match your database structure Add notification nodes (Slack, Email) to alert you when new companies are added

🧩 Jamf Smart Group Membership to Slack Automatically export Jamf smart group membership to Slack in CSV format. Perfect for IT and security teams who need fast visibility into device grouping—without manually logging into Jamf. Slack automatically parses the CSV, making it viewable directly in the chat—no download required. ✅ Prerequisites • A Jamf Pro API key with permissions to read smart groups and computer details • A Slack app or incoming webhook URL with permission to post messages to your desired channel 🔍 How it works • Manually trigger the flow or connect it to a webhook • Fetch the list of smart group IDs (set manually in the workflow) • Loop over each group to get its members • Use a sub-workflow to fetch detailed info for each device • Convert the member list to CSV • Post the CSV file to a Slack channel ⚙️ Set up steps • Takes ~5–10 minutes to configure • Set your Jamf BaseURL and group IDs in the Set nodes • Add your Jamf Pro API credentials to the HTTP Request nodes • Provide your Slack webhook token or channel ID in the Slack node • Optional: Customize CSV fields or formatting as needed

CallForge - AI Gong Transcript PreProcessor Transform your Gong.io call transcripts into structured, enriched, and AI-ready data for better sales insights and analytics. Who is This For? This workflow is designed for: ✅ Sales teams looking to automate call transcript formatting. ✅ Revenue operations (RevOps) professionals optimizing AI-driven insights. ✅ Businesses using Gong.io that need structured, enriched call transcripts for better decision-making. What Problem Does This Workflow Solve? Manually processing raw Gong call transcripts is inefficient and often lacks essential context for AI-driven insights. With CallForge, you can: ✔ Extract and format Gong call transcripts for structured AI processing. ✔ Enhance metadata using sales data from Salesforce. ✔ Classify speakers as internal (sales team) or external (customers). ✔ Identify external companies by filtering out free email domains (e.g., Gmail, Yahoo). ✔ Enrich customer profiles using PeopleDataLabs to identify company details and locations. ✔ Prepare transcripts for AI models by structuring conversations and removing unnecessary noise. What This Workflow Does 1. Retrieves Gong Call Data Calls the Gong API to extract call metadata, speaker interactions, and collaboration details. Fetches call transcripts for AI processing. 2. Processes and Cleans Transcripts Converts call transcripts into structured, speaker-based dialogues. Assigns each speaker as either Internal (Sales Team) or External (Customer). 3. Extracts Company Information Retrieves Salesforce data** to match customers with existing sales opportunities. Filters out free email domains* to determine the *customer’s actual company domain**. Calls the PeopleDataLabs API to retrieve additional company data and location details. 4. Merges and Enriches Data Combines Gong metadata, Salesforce customer details and insights**. Ensures all necessary data is available for AI-driven sales insights. 5. Final Formatting for AI Processing Merges all call transcript data into a single structured format for AI analysis. Extracts the final cleaned, enriched dataset for further AI-powered insights. How to Set Up This Workflow 1. Connect Your APIs 🔹 Gong API Access – Set up your Gong API credentials in n8n. 🔹 Salesforce Setup – Ensure API access if you want customer enrichment. 🔹 PeopleDataLabs API – Required to retrieve company and location details based on email domains. 🔹 Webhook Integration – Modify the webhook call to push enriched call data to an internal system. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion How to Customize This Workflow 💡 Modify Data Sources – Connect different CRMs (e.g., HubSpot, Zoho) instead of Salesforce. 💡 Expand AI Analysis – Add another AI model (e.g., OpenAI GPT, Claude) for advanced conversation insights. 💡 Change Speaker Classification Rules – Adjust internal vs. external speaker logic to match your team’s structure. 💡 Filter Specific Customers – Modify the free email filtering logic to better fit your company’s needs. Why Use CallForge? 🚀 Automate Gong call transcript processing to save time. 📊 Improve AI accuracy with enriched, structured data. 🛠 Enhance sales strategy by extracting actionable insights from calls. Start optimizing your Gong transcript analysis today!

This n8n template allows you to use AI to generate logos or images which mimic visual styles of other logos or images. The model used to generate the images is Google's Imagen 3.0. With this template, users will be able to automate design and marketing tasks such as creating variants of existing designs, remixing existing assets to validate different styles and explore a range of designs which would have been otherwise too expensive and time-consming previously. How it works A form trigger is used to capture the source image to reference styles from and a prompt for the target image to generate. The source image is passed to Gemini 2.0 to be analysed and its visual style and tone extracted as a detailed description. This visual style description is then combined with the user's initial target image prompt. This final prompt is given to Imagen 3.0 to generate the images. A quick webpage is put together with the generated images to present back to the user. If the user provided an email address, a copy of this HTML page will be sent. How to use Ensure the workflow is live to share the form publicly. The source image must be accessible to your n8n instance - either a public image of the internet or within your network. For best results, select a source image which has strong visual identity as these will allow the LLM to better describe it. For your prompt, refer to the imagen prompt guide found here: https://ai.google.dev/gemini-api/docs/image-generation#imagen-prompt-guide Requirements Gemini for LLM and Imagen model. Cloudinary for image CDN. Gmail for email sending. Customising this workflow Feel free to swap any of these out for tools and services you prefer. Want to fully automate? Switch the form trigger for a webhook trigger!

How it works Transform your business with intelligent deal monitoring and automated customer engagement! This AI-powered coupon aggregator continuously tracks competitor deals and creates personalized marketing campaigns that convert. Key Steps 24/7 Deal Monitoring - Automatically scans competitor websites daily for the best deals and offers Smart Customer Segmentation - Uses AI to intelligently categorize and target your customer base Personalized Offer Generation - Creates tailored coupon campaigns based on customer behavior and preferences Automated Email Marketing - Sends targeted email campaigns with personalized deals to the right customers Performance Analytics - Tracks campaign performance and provides detailed insights and reports Daily Management Reports - Delivers comprehensive analytics to management team every morning Set up steps Setup time: 10-15 minutes Configure competitor monitoring - Add target websites and deal sources you want to track Set up customer database - Connect your customer data source for intelligent segmentation Configure email integration - Connect your email service provider for automated campaigns Customize deal criteria - Define what types of deals and offers to prioritize Set up analytics tracking - Configure Google Sheets or database for performance monitoring Test automation flow - Run a test cycle to ensure all integrations work smoothly Never miss a profitable deal opportunity - let AI handle the monitoring and targeting while you focus on growth!

Compare Local Ollama Vision Models for Image Analysis using Google Docs Process images using locally hosted Ollama Vision Models to extract detailed descriptions, contextual insights, and structured data. Save results directly to Google Docs for efficient collaboration. Who is this for? This workflow is ideal for developers, data analysts, marketers and AI enthusiasts who need to process and analyze images using locally hosted Ollama Vision Language Models. It’s particularly useful for tasks requiring detailed image descriptions, contextual analysis, and structured data extraction. What problem is this workflow solving? / Use Case The workflow solves the challenge of extracting meaningful insights from images in exhaustive detail, such as identifying objects, analyzing spatial relationships, extracting textual elements, and providing contextual information. This is especially helpful for applications in real estate, marketing, engineering, and research. What this workflow does This workflow: Downloads an image file from Google Drive. Processes the image using multiple Ollama Vision Models (e.g., Granite3.2-Vision, Gemma3, Llama3.2-Vision). Generates detailed markdown-based descriptions of the image. Saves the output to a Google Docs file for easy sharing and further analysis. Setup Ensure you have access to a local instance of Ollama. https://ollama.com/ Pull the Ollama vision models. Configure your Google Drive and Google Docs credentials in n8n. Provide the image file ID from Google Drive in the designated node. Update the list of Ollama vision models Test the workflow by clicking ‘Test Workflow’ to trigger the process. How to customize this workflow to your needs Replace the image source with another provider if needed (e.g., AWS S3 or Dropbox). Modify the prompts in the "General Image Prompt" node to suit specific analysis requirements. Add additional nodes for post-processing or integrating results into other platforms like Slack or HubSpot. Key Features: Detailed Image Analysis**: Extracts comprehensive details about objects, spatial relationships, text elements, and contextual settings. Multi-Model Support**: Utilizes multiple vision models dynamically for optimal performance. Markdown Output**: Formats results in markdown for easy readability and documentation. Google Drive Integration**: Seamlessly downloads images and saves results to Google Docs.

This workflow template, "Chinese Translator via Line x OpenRouter (Text & Image)" is designed to provide seamless Chinese translation services directly within the LINE messaging platform. By integrating with OpenRouter.ai and advanced language models like Qwen, this workflow translates text or images containing Chinese characters into pinyin and English translations, making it an invaluable tool for language learners, travelers, and businesses operating in multilingual environments. This template is ideal for: Language Learners: Who want to practice Chinese by receiving instant translations of text or images. Travelers: Looking for quick translations of Chinese signs, menus, or documents while abroad. Educators: Teaching Chinese language courses and needing tools to assist students with translations. Businesses: Operating in multilingual markets and requiring efficient communication tools. Automation Enthusiasts: Seeking to build intelligent chatbots that can handle language translation tasks. What Problem Does This Workflow Solve? Translating Chinese text or images into English and pinyin can be challenging, especially for beginners or those without access to reliable translation tools. This workflow solves that problem by: Automatically detecting and translating text or images containing Chinese characters. Providing accurate translations in both pinyin and English for better comprehension. Supporting multiple input formats (text, images) to cater to diverse user needs. Sending replies directly to users via the LINE messaging platform , ensuring accessibility and ease of use. What This Workflow Does 1) Receive Messages via LINE Webhook The workflow is triggered when a user sends a message (text, image, or other types) to the LINE bot. 2) Display Loading Animation A loading animation is displayed to reassure the user that their request is being processed. 3) Route Input Types The workflow uses a Switch node to determine the type of input (text, image, or unsupported formats). If the input is text , it is sent to the OpenRouter.ai API for translation. If the input is an image , the workflow extracts the image content, converts it to base64, and sends it to the API for translation. Unsupported formats trigger a polite response indicating the limitation. 4) Translate Content Using OpenRouter.ai The workflow leverages Qwen models from OpenRouter.ai to generate translations: For text inputs, it provides Chinese characters , pinyin , and English translations . For images, it extracts and translates using the qwen-VL model which can take images 5) Reply with Translations The translated content is formatted and sent back to the user via the LINE Reply API. Setup Guide Pre-Requisites Access to the LINE Developers Console to configure your webhook and channel access token. An OpenRouter.ai account with credentials to access Qwen models. Basic knowledge of APIs, webhooks, and JSON formatting. Step-by-Step Setup 1) Configure the LINE Webhook: Go to the LINE Developers Console and set up a webhook to receive incoming messages. Copy the Webhook URL from the Line Webhook node and paste it into the LINE Console. Remove any "test" configurations when moving to production. 2) Set Up OpenRouter.ai: Create an account on OpenRouter.ai and obtain your API credentials. Connect your credentials to the OpenRouter nodes in the workflow. 3) Test the Workflow: Simulate sending text or images to the LINE bot to verify that translations are processed and replied correctly. How to Customize This Workflow to Your Needs Add More Languages: Extend the workflow to support additional languages by modifying the API calls. Enhance Image Processing: Integrate more advanced OCR tools to improve text extraction from complex images. Customize Responses: Modify the reply format to include additional details, such as grammar explanations or cultural context. Expand Use Cases: Adapt the workflow for specific industries, such as tourism or e-commerce, by tailoring the translations to relevant vocabulary. Why Use This Template? Real-Time Translation: Provides instant translations of text and images, improving user experience and accessibility. Multimodal Support: Handles both text and image inputs, catering to diverse user needs. Scalable: Easily integrate into existing systems or scale to support multiple users and workflows. Customizable: Tailor the workflow to suit your specific audience or industry requirements.