Workflow Templates

Who is this for? This template is designed for anyone who wants to integrate MCP with their AI Agents using Airtable. Whether you're a developer, a data analyst, or an automation enthusiast, if you're looking to leverage the power of MCP and Airtable in your n8n workflows, this template is for you. What problem is this workflow solving? This template caters to MCP beginners seeking a hands-on example and developers looking to integrate Airtable MCP service. When integrating MCP with Airtable, manually updating AI Agents after changes to Airtable data on the MCP Server is time-consuming and error-prone. This template automates the process, enabling the AI Agent to instantly recognize changes made to Airtable on the MCP Server. In data management, for example, it ensures that record updates or additions in Airtable are automatically detected by the AI Agent. With detailed steps, it simplifies the integration process for all users. What this workflow does This workflow focuses on integrating MCP with Airtable within n8n. Specifically, it allows you to build an MCP Server and Client using Airtable nodes in n8n. Any changes made to the Airtable Base/Table on the MCP Server are automatically recognized by the MCP Client in the workflow. This means that you can make changes to your Airtable (such as adding, deleting, or modifying records) on the MCP Server, and the MCP Client in the n8n workflow will immediately detect these changes without any manual intervention. Setup Requirements An active n8n account. Access to Airtable API. A sample base and rows in Airtable that you can use to test. An API key from your preferred LLM to power the AI agent. Step-by-step guide Create a new workflow in n8n: Log in to your n8n account and create a new workflow. Add Airtable nodes: Search for and add the Airtable nodes to your workflow that you wish the MCP client to have access to. Set up the MCP Server and Client: Use the appropriate nodes in n8n to set up the MCP Server and Client. Connect the Airtable nodes to the MCP nodes as required. Activate and test the workflow: Talk to the chat trigger once all credentials have been updated and table data synced and try adding some rows, deleting or finding and updating cells. How to customize this workflow to your needs If you want to customize this workflow, you can: Modify the triggers:** You can change the conditions under which the MCP Client detects changes. For example, you can set it to detect changes only in specific fields or based on certain record values in Airtable. Integrate with other services:** You can add more nodes to the workflow to integrate with other services, such as sending notifications to Slack or triggering further actions based on the detected Airtable changes. Need help? Feel free to contact us at 1 Node. Get instant access to a library of free resources we created.

This workflow syncs Outlook Calendar events to a Notion database. The Outlook Calendar event must be within a specific time frame (default of within next year) for the workflow to pick up the event. The event subject will be the title of the Notion page, and the event link will be added to the Notion page as a property. Prerequisites Notion account and Notion credentials. Microsoft account and Microsoft credentials. How it works On scheduled intervals, find all Outlook Calendar events within a specific time frame. For each event, check if the event already exists in the Notion database. If it does not exist, create a new page in the Notion database, otherwise update the existing page. Setup This workflow requires that you set up a Notion database or use an existing one with at least the following fields: Title (title) Date (date) Event ID (text) Link (URL)

n8n Creators Template: Creator Profile Stats Updater This n8n workflow template is designed to automate the process of updating a creator's profile statistics, including total workflows, complex workflows, approved workflows, pending workflows, total nodes, and total views. It utilizes various nodes to fetch data, process it, and update a SVG file hosted on GitHub to reflect the latest stats. Workflow Overview Schedule Trigger: Triggers the workflow execution at specified intervals. Config: Sets up configuration details like creator username, colors for text, icons, border, and card. Get Workflows: Fetches workflows associated with the creator from the n8n API. Workflows Data: Processes the fetched data to calculate various statistics. Get User: Fetches user details from the n8n API. Download Image: Downloads the creator's profile image. Extract From File: Extracts binary data from the downloaded image file. SVG: Generates an SVG file with updated stats and visual representation. GitHub: Commits the updated SVG file to the specified GitHub repository. Final: Prepares the final data set for further processing or output. Sticky Note: Provides a visual note or reminder within the workflow editor. Embed & Live Preview Since it's a .SVG format you can host it anywhere. treat it like normal image so you can embed it with any site, forum, page that support posting images. here's example code for markdown: Here's the result Or served through CDN & Cache Setup Instructions GitHub Credentials: Ensure you have GitHub credentials set up in your n8n instance to allow the workflow to commit changes to your repository. Configure Trigger: Adjust the Schedule Trigger node to set the desired execution intervals for the workflow. Set Configuration: Customize the Config node with your GitHub username and preferred aesthetic options for the SVG. Deploy Workflow: Import the workflow into your n8n instance and deploy it. Customization Options Text and Icon Colors**: Customize the colors used in the SVG by modifying the respective fields in the Config node. Profile Image Size**: Adjust the image size in the Download Image node URL if needed. Commit Messages**: Modify the commit messages in the GitHub nodes to suit your version control conventions [I've used $now funaction to include current time in message which will gives allways a diffrent commit value]. Requirements n8n (Self-hosted or Cloud version compatible with 2024 releases and up) GitHub account and repository Basic understanding of n8n workflow configuration Support and Contributions For support, please refer to the n8n community forum or the official n8n documentation. Contributions to the template can be made you're allowed to reuse this workflow and reshare with edit (like new design/colors etc..) under your name.

. IOT device control with MQTT and webhook This workflow is for users wanting a practical example of how to control IOT systems using the MQTT protocol in an an n8n environment. The template provides typical n8n MQTT and Webhook node implementation and configuration settings necessary to set IOT device inputs and outputs. How it works A webpage with IOT control 'on and 'off' buttons is presented to the user. When a button is selected on the webpage the value is sent via a webhook to trigger the active workflow. The workflow set node then prepares the received value into a message payload. It then passes the message to the MQTT node for publishing the topic with the payload to a cloud based MQTT broker. A remote ESP32 micro-controller subscribes to the broker and reads the payload contained in the topic. The ESP32 will then toggle the GPIO pin depending on the topic payload value. The IOT control webpage The webpage is a simple HTML page containing the clickable 'on' and 'off' buttons. It also has the get webhook URL that sends the selected value to the n8n workflow in this case running locally. The URL webhook format is http://localhost:5678/webhook/pin-control?value=action The webpage code IOT-control.html IOT device The IOT device is an ESP32 micro-controller running on a remote network. To keep it simple GPIO2 is selected as the control output. In this case when the received value is "on" GPIO2 goes high a led will turn on in the ESP32. It will go off when the received value is "off". The program for the ESP32 IOT control is 'main.py' . You will require a micropython interpreter to be uploaded to the ESP32 for the program to run automatically. The code can be easily edited and modified to accommodate any further attached IOT devices. The ESP32 main.py code main.py How to customise this workflow to your needs ESP32 You will need a working ESP32 installed with a micro-python interpreter. The code main.py is provided. The main.py program can loaded and edited with a python IDE. I used Thonny for this example. Use a free MQTT broker to get started. I used "broker.emqx.io" in the code. IOT Control Webpage The webpage contains HTML and can be easily edit to enhance functionality. The embedded webhook is configured for n8n production mode. http://localhost:5678/webhook/pin-control?value=action If you want to run the page in test mode you will use the following URL. http://localhost:5678/webhook-test/pin-control?value=action n8n workflow. The workflow is a good demonstration of how to control IOT devices using n8n. Following these steps will give a good insight for microcontroller automation.

Automated pipeline to collect and analyze investor data from Crunchbase, tracking investment patterns, funding history, and portfolio companies for market analysis and lead generation. 🚀 What It Does Investor Profiling**: Collects comprehensive data on investors and VC firms Investment Pattern Analysis**: Tracks funding history and investment preferences Portfolio Monitoring**: Keeps tabs on investor portfolios and new investments Data Enrichment**: Enhances raw data with additional context and metrics 🎯 Perfect For Startup founders seeking investors Market research analysts Investment professionals Business development teams Competitive intelligence ⚙️ Key Benefits ✅ Comprehensive investor profiles ✅ Real-time investment tracking ✅ Market trend analysis ✅ Data-driven investment decisions ✅ Time-saving automation 🔧 What You Need Crunchbase API access n8n instance Storage solution (database or spreadsheet) 📊 Data Points Collected Investor/Firm details Investment history Portfolio companies Funding rounds participated in Investment focus areas Contact information (when available) 🛠️ Setup & Support Quick Setup Deploy in 30 minutes with our step-by-step configuration guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Transform your investor research with automated data collection and analysis. Spend less time gathering data and more time making strategic decisions.

AI-Agent Code Review for GitHub Pull Requests Description: This n8n workflow automates the process of reviewing code changes in GitHub pull requests using an OpenAI-powered agent. It connects your GitHub repo, extracts modified files, analyzes diffs, and uses an AI agent to generate a code review based on your internal code best practices (fed from a Google Sheet). It ends by posting the review as a comment on the PR and tagging it with a visual label like ✅ Reviewed by AI. 🔧 What It Does Triggered on PR creation Extracts code diffs from the PR Formats and feeds them into an OpenAI prompt Enriches the prompt using a Google Sheet of Swift best practices Posts an AI-generated review as a comment on the PR Applies a PR label to visually mark reviewed PRs ✅ Prerequisites Before deploying this workflow, ensure you have the following: n8n Instance (Self-hosted or Cloud) GitHub Repository with PR activity OpenAI API Key** for GPT-4o, GPT-4-turbo, or GPT-3.5 GitHub OAuth App** (or PAT) connected to n8n to post comments and access PR diffs (Optional) Google Sheets API credentials if using the code best practices lookup node. ⚙️ Setup Instructions 1. Import the Workflow in n8n, click on Workflows → Import from file or JSON Paste or upload the JSON code of this template 2. Configure Triggers and Connections 🔁 GitHub Trigger Node**: PR Trigger Repository**: Select the GitHub repo(s) to monitor Events**: Set to pull_request Auth**: Use GitHub OAuth2 credentials 📥 HTTP Request Node: Get file's Diffs from PR No authentication needed; it uses dynamic path from trigger 🧠 OpenAI Model Node**: OpenAI Chat Model Model**: Select gpt-4o, gpt-4-turbo, or gpt-3.5-turbo Credential**: Provide your OpenAI API Key 🧑‍💻 Code Review Agent Node : Code Review Agent Connected to OpenAI and optionally to tools like Google Sheets 💬 GitHub Comment Poster Uses GitHub API to post review comments back on PR Node: GitHub Robot Credential: Use the agent Github account (OAuth or PAT) Repo : Pick your owen Github Repository 🏷️ PR Labeler (optional) Adds label ReviewedByAI after successful comment Node: Add Label to PR Label : you ca customize the label text of your owen tag. 📊 Google Sheet Best Practices config (optional) Connects to a Google Sheet for coding guideline lookups, we can replace Google sheet by another tool or data base First prepare your best practices list with the clear description and the code bad/good examples Add al the best practices in your Google Sheet Configure* the Code *Best Practices node** in the template : Credential : Use your Google Sheet account by OAuth2 URL : Add your Google Sheet document URL Sheet : Add the name of the best practices sheet

A fully automated content engine that researches, writes, scores, and visualizes LinkedIn posts — built with n8n, OpenAI, Perplexity, and Replicate. What it does: ✅ Researches any topic using real-time data ✅ Writes a personalized post in your voice ✅ Refines tone and structure ✅ Generates abstract, high-quality visual assets ✅ Scores the output and saves it to Google Sheets How it works: Triggered when you change a row status in Google Sheets Uses Perplexity to research GPT-4o (OpenAI) to create and polish content Replicate (FLUX Pro) to generate images Scores the post using heuristics Appends everything back to your sheet

Template Information Who is this template for? This template is for users looking to retrieve email information from LinkedIn profiles and update Google Sheets with the collected data. 🎥 quick set up video How it works** The template utilizes a series of nodes to fetch email information from LinkedIn profiles. It starts with a Schedule Trigger node that sets the interval for the workflow. The Conditional Check node verifies if certain fields like Name, Gender, Job Title, Summary, and LinkedIn URL are not empty. The HTTP Request node sends a POST request to the specified URL with API key and profile information. The Data Merge node merges the data collected. The Field Editing node modifies the fields as needed. Finally, the Google Sheets Update node updates the Google Sheets with the gathered information. Set Up Instructions Make sure to have the necessary credentials and permissions for accessing LinkedIn and Google Sheets. Set up the API key required for the HTTP Request node. Configure the Google Sheets Update node with the appropriate document ID and sheet name. Check and adjust field mappings in the Field Editing node according to your needs. Run the workflow and monitor the updates in your Google Sheets document. Overview: The workflow is designed to find contact information for LinkedIn profile URLs stored in a Google Sheet. It involves various nodes for different operations such as making HTTP requests, scheduling triggers, reading from and updating Google Sheets, field editing, data merging, and conditional checks. A video demonstrating the workflow process can be accessed here. Copy this template to get started : Google Sheets Using Prospeo.io LinkedIn Email Finder API with cURL To use the API endpoint "https://api.prospeo.io/linkedin-email-finder" with cURL, follow these steps: Use the cURL command with the following parameters: curl -X POST \ -H "Content-Type: application/json" \ -H "X-KEY: your_api_key" \ -d '{ "url": "https://www.linkedin.com/in/john-doe/" }' \ "https://api.prospeo.io/linkedin-email-finder" Replace "your_api_key" with your actual API key. Update the "url" field in the JSON data with the LinkedIn profile URL for which you want to find the email address. To get access to this API and obtain your API key, you need to sign up on the Prospeo platform and subscribe to their LinkedIn email finder service. Once you have subscribed, you will receive an API key that you can use to authenticate your requests to the API endpoint. Description: Schedule Trigger:** Triggers the workflow based on a defined schedule interval, in this case, based on minutes. Schedule Trigger Node Documentation Google Sheets Read:** Reads data from a Google Sheets document and sheet based on the provided document ID and sheet name. Google Sheets Node Documentation Conditional Check:** Checks multiple conditions based on the input data and performs actions accordingly. Conditional Node Documentation HTTP Request:** Sends an HTTP POST request to a specified URL with headers and body parameters. HTTP Request Node Documentation No Operation, do nothing:** Placeholder node that does not perform any operation. Data Merge:** Merges data based on specified mode and combination settings. Merge Node Documentation Field Editing:** Edits fields by setting specific values for each field based on input data. Set Node Documentation Google Sheets Update:** Updates data in a Google Sheets document and sheet based on specified columns and values. Google Sheets Node Documentation

Example: @SubAlertMe_Bot Summary: The automated image analysis and response workflow using n8n is a sophisticated solution designed to streamline the process of analyzing images sent via Telegram and delivering insightful responses based on the analysis outcomes. This cutting-edge workflow employs a series of meticulously orchestrated nodes to ensure seamless automation and efficiency in image processing tasks. Use Cases: This advanced workflow caters to a myriad of scenarios where real-time image analysis and response mechanisms are paramount. The use cases include: Providing immediate feedback on images shared within Telegram groups. Enabling automated content moderation based on the analysis of image content. Facilitating rapid categorization and tagging of images based on the results of the analysis. Detailed Workflow Setup: To effectively implement this workflow, users must adhere to a meticulous setup process, which includes: Access to the versatile n8n platform, ensuring seamless workflow orchestration. Integration of a Telegram account to facilitate image reception and communication. Utilization of an OpenAI account for sophisticated image analysis capabilities. Configuration of Telegram and OpenAI credentials within the n8n environment for seamless integration. Proficiency in creating and interconnecting nodes within the n8n workflow for optimal functionality. Detailed Node Description: Get the Image (Telegram Trigger): Actively triggers upon receipt of an image via Telegram, ensuring prompt processing. Extracts essential information from the received image message to initiate further actions. Merge all fields To get data from trigger: Seamlessly amalgamates all relevant data fields extracted from the trigger node for comprehensive data consolidation. Analyze Image (OpenAI): Harnesses the powerful capabilities of OpenAI services to conduct in-depth analysis of the received image. Processes the image data in base64 format to derive meaningful insights from the visual content. Aggregate all fields: Compiles and consolidates all data items for subsequent processing and analysis, ensuring comprehensive data aggregation. Send Content for the Analyzed Image (Telegram): Transmits the analyzed content back to the Telegram chat interface for seamless communication. Delivers the analyzed information in textual format, enhancing user understanding and interaction. Switch Node: The Switch node is pivotal for decision-making based on predefined conditions within the workflow. It evaluates incoming data to determine the existence or absence of specific elements, such as images in this context. Utilizes a set of rules to assess the presence of image data in the message payload and distinguishes between cases where images are detected and when they are not. This crucial node plays a pivotal role in directing the flow of the workflow based on the outcomes of its evaluations. Conclusion: The automation of image analysis processes through this sophisticated workflow not only enhances operational efficiency but also revolutionizes communication dynamics within Telegram interactions. By incorporating this advanced workflow solution, users can optimize their image analysis workflows, bolster communication efficacy, and unlock new levels of automation in image processing tasks.

Template for Kids' Story in Arabic The n8n template for creating kids' stories in Arabic offers a versatile platform for storytellers to captivate young audiences with educational and interactive tales. It allows for customization to suit various use cases and can be set up effortlessly. Check this example: https://t.me/st0ries95 Use Cases Educational Platforms: Educational platforms can automate the creation and distribution of educational stories in Arabic for children using this template. By incorporating visual and auditory elements into the storytelling process, educational platforms can enhance learning experiences and engage young learners effectively. Children's Libraries: Children's libraries can utilize this template to curate and share a diverse collection of Arabic stories with young readers. The automated generation of visual content and audio files enhances the storytelling experience, encouraging children to immerse themselves in new worlds and characters through captivating narratives. Language Learning Apps: Language learning apps focused on Arabic can integrate this template to offer culturally rich storytelling experiences for children learning the language. By translating stories into Arabic and supplementing them with visual and auditory components, these apps can facilitate language acquisition in an enjoyable and interactive manner. Configuration Guide for Nodes OpenAI Chat Model Nodes: Functionality**: Allows interaction with the OpenAI GPT-4 Turbo model. Purpose**: Enables communication with advanced chat capabilities. Create a Prompt for DALL-E Node: Customization**: Tailor prompts for generating relevant visual content. Summarization**: Define prompts for visual content generation without text. Generate an Image for the Story Node: Resource Type**: Specifies image as the resource. Prompt Setup**: Configures prompt for textless image creation within the visual content. Generate Audio for the Story Node: Resource Type**: Chooses audio as the resource. Input Definition**: Sets input text for audio file generation. Translate the Story to Arabic Node: Chunking Mode Selection**: Allows advanced chunking mode choice. Summarization Configuration**: Sets method and prompts for story translation into Arabic. Send the Story To Channel Node: Channel ID**: Specifies the channel ID for sending the story text. Text Configuration**: Sets up the text to be sent to the channel. By following these node descriptions, users can effectively configure the n8n template for kids' stories in Arabic, tailoring it to specific use cases for a seamless and engaging storytelling experience for young audiences.

Description This intelligent n8n automation streamlines the process of collecting, extracting, and scoring resumes sent to a Gmail inbox—making it an ideal solution for recruiters who regularly receive hundreds of applications. The workflow scans incoming emails with attachments, extracts relevant candidate information from resumes using AI, evaluates each candidate based on customizable criteria, and logs their scores alongside contact details in a connected Google Sheet. Who Is This For? Recruiters & Hiring Managers**: Automate the resume screening process and save hours of manual work. HR Teams at Startups & SMBs**: Quickly evaluate talent without needing large HR ops infrastructure. Agencies & Talent Acquisition Firms**: Screen large volumes of resumes efficiently and with consistent criteria. Solo Founders Hiring for Roles**: Use AI to help score and shortlist top candidates from email applications. What Problem Does This Workflow Solve? Manually reviewing resumes is time-consuming, error-prone, and inconsistent. This workflow solves these challenges by: Automatically detecting and extracting resumes from Gmail attachments. Using OpenAI to intelligently extract candidate info from unstructured PDFs. Scoring resumes using customizable evaluation criteria (e.g., relevant experience, skills, education). Logging all candidate data (Name, Email, LinkedIn, Score) in a centralized, filterable Google Sheet. Enabling faster, fairer, and more efficient candidate screening. How It Works 1. Gmail Trigger Runs on a scheduled interval (e.g., every 6 or 24 hours). Scans a connected Gmail inbox (using OAuth credentials) for unread emails that contain PDF attachments. 2. Extract Attachments Downloads the attached resumes from matching emails. 3. Parse Resume Text Sends the PDF file to OpenAI's API (via GPT-4 or GPT-3.5 with file support or via base64 + PDF-to-text tool). Prompts GPT with a structured format to extract fields like Name, Email, LinkedIn, Skills, and Education. 4. Score Resume Evaluates the resume on predefined scoring logic using AI or logic inside the workflow (e.g., "Has X skill = +10 points"). 5. Log to Google Sheets Appends a new row in a connected Google Sheet, including: Candidate Name Email Address LinkedIn URL Resume Score Setup Accounts & API Keys You’ll need accounts and credentials for: n8n** (hosted or self-hosted) Google Cloud Platform** (for Gmail, Drive, and Sheets APIs) OpenAI** (for GPT model access) Google Sheet Make a Google Sheet and connect it via Google Sheets node in n8n. Columns should include: Name Email LinkedIn Score Configuration Google Cloud: Enable Gmail API and Google Sheets API. Set up OAuth 2.0 Credentials in Google Console. Connect n8n Gmail, Drive, and Sheets nodes to these credentials. OpenAI: Generate an API Key. Use the HTTP Request node or official OpenAI node to send prompt requests. n8n Workflow: Add Gmail Trigger. Add extraction logic (e.g., filter PDFs). Add OpenAI prompt for resume parsing and scoring. Connect structured output to a Google Sheets node. Requirements Accounts: n8n** Google** (Gmail, Sheets, Drive, Cloud Console) OpenAI** API Keys & Credentials: OpenAI API Key Google Cloud OAuth Credentials Gmail Access Scopes (for reading attachments) Configured Google Sheet OpenAI usage (after free tier) Google Cloud API usage (if exceeding free quota)

🚀 Transform LinkedIn Post Reactions into Content Ideas with Airtable 📝 Description This workflow helps you to turn your LinkedIn activity into a powerful content ideation engine. It captures your most recent post reactions on LinkedIn automatically, filters them based on recency, and structures the content into Airtable—ready for brainstorming, inspiration, or publication planning. ⚙️ What It Does Fetches* the latest liked posts from LinkedIn via a public API (rapidapi.com/Real-Time Linkedin Scraper*). Filters** posts to include only those marked as your decided reaction and posted in the last 7 days. Extracts** the post text, author, links and more. Formats** the data into a database-friendly structure. Saves** the output in Airtable for easy tracking, tagging, or team collaboration. 💡 Use Cases Build a content idea vault from posts you admire. Capture inspiration from thought leaders. Identify trends based on what you find insightful. Supercharge your personal brand or newsletter by turning likes into learning. 🛠 Prerequisites Before using this template, make sure you have: ✅ A RapidAPI account and access to the linkedin-api8 endpoint. ✅ Your RapidAPI key and the target LinkedIn username. ✅ An Airtable account with a base/table set up. 🧰 Setup Instructions Clone this template into your n8n instance. Open the Fetch LinkedIn Likes node and enter: Your LinkedIn username. Your RapidAPI key in the headers. Open the Save to Airtable node and: Connect your Airtable account. Link the correct base (Content Hub) and table (Ideas). Set your desired schedule in the Trigger node. Activate the workflow and you're done! 📋 Airtable Setup Create a base called Content Hub and a table named Ideas with the following columns: | Column Name | Type | Required | Notes | |-------------|------------|----------|----------------------------| | Title | Single line text | ✅ | Generated from author info | | Description | Long text | ✅ | Contains post content | | Source | URL | ✅ | Link to the original post | | Type | Single select | ✅ | Value: Linkedin