Workflow Templates

Who this is for This workflow is for Amazon affiliate marketers and social media managers who want to quickly turn product links into engaging Facebook posts with AI-generated captions and images — fully automated. What this workflow does This workflow starts every time a new Product Link is added to a connected Google Sheet. It then: Extracts the ASIN** from the product link. Fetches product details** from Amazon using RapidAPI. Generates a short, scroll-stopping Facebook caption** with OpenRouter AI. Creates a product image prompt** and sends it to Google Gemini for high-quality image generation. Uploads the creative directly to Facebook** via the Facebook Graph API. Marks the Google Sheet row** as “Done ✅” after posting. The Facebook post includes: Product image (AI-enhanced) Short, benefit-focused caption with emojis Affiliate link Setup To set this template up, follow the sticky notes inside the workflow and: Google Sheets → Connect your sheet and ensure the columns “Product Link” & “Facebook Upload” exist. RapidAPI → Add your API key in the “Amazon Product Details” node. OpenRouter → Add credentials for caption generation. Google Gemini → Add your API key for image generation. Facebook Graph API → Connect your Facebook account for posting. How to customize this workflow to your needs Change the Facebook caption prompt to match your tone or branding. Adjust the AI image generation prompt to fit your preferred photography style. Modify the Google Sheet update logic if you want to track additional info (e.g., posting date, engagement stats). Switch Facebook posting to Instagram or another platform by replacing the final API call.

Who is it for? This workflow is perfect for anyone who wants to: Automatically collect contacts from Google Maps**: emails, phone numbers, websites, social media (LinkedIn, Facebook), city, ratings, and reviews. Organize everything neatly in Airtable**, without dealing with messy CSV exports that cause headaches. Send a personalized email to each lead**, without writing it or hitting “send” yourself. 👉 In short, it’s the perfect tool for marketing agencies, freelancers in prospecting, or sales teams tired of endless copy-paste. If you want to automate manual tasks, visit our French agency 0vni – Agence automatisation. How does it work? Here’s the pipeline: Scrape Google Maps with Apify (business name, email, website, phone, LinkedIn, Facebook, city, rating, etc.). Clean and map the data so everything is well-structured (Company, Email, Phone, etc.). Send everything into Airtable to build a clear, filterable database. Trigger an automatic email via Gmail, personalized for each lead. 👉 The result: a real prospecting machine for local businesses. What you need before starting ✅ An Apify account (for Google Maps scraping). ✅ An Airtable account with a prepared base (see structure below). ✅ A Gmail account (to send automatic emails). Airtable Base Structure Your table should contain the following columns: | Company | Email | Phone Number | Website | LinkedIn | Facebook | City | Category | Google Maps Reviews | Google Maps Link | | ------- | ---------------------------------------- | ----------------- | -------------------------------------------- | -------------- | -------------- | ---------------- | ---------------- | ------------------- | ----------------- | | 4 As | contact@4-as.fr | +33 1 89 36 89 00 | https://www.4-as.fr/ | linkedin.com/… | facebook.com/… | 94100 Saint-Maur | training, center | 48 reviews / 5 ★ | maps.google.com/… | Detailed Workflow Steps Step 1 – GO Trigger Node**: Manual Trigger Purpose**: Start the workflow manually. 👉 You can replace this trigger with a Webhook (to launch the flow via a URL) or a Cron (to run it automatically on a schedule). Step 2 – Scrape Google Maps Node**: HTTP Request Method**: POST Where to find the Apify URL? Go to Google Maps Email Leads Fast Scraper Click on API (top right) Open API Endpoints Copy the URL of the 3rd option: Run Actor synchronously and get dataset items 👉 This URL already includes your Apify API token. Body Content Type: JSON Body JSON (example)**: Body Content Type**: JSON Body JSON (example)**: *{ "area_height": 10, "area_width": 10, "emails_only": true, "gmaps_url": "https://www.google.com/maps/search/training+centers+near+Amiens/", "max_results": 200, "search_query": "training center" }* Step 3 – Wait Node**: Wait Purpose**: Give the scraper enough time to return data. Recommended delay*: *10 seconds (adjust if needed). 👉 This ensures that Apify has finished processing before we continue. Step 4 – Mapping Node**: Set Purpose**: Clean and reorganize the raw dataset into structured fields that match Airtable columns. Assignments (example): Company = {{ $json.name }} Email = {{ $json.email }} Phone = {{ $json.phone_number }} Website = {{ $json.website_url }} LinkedIn = {{ $json.linkedin }} Facebook = {{ $json.facebook }} City = {{ $json.city }} Category = {{ $json.google_business_categories }} Google Maps Reviews = {{ $json.reviews_number }} reviews, rating {{ $json.review_score }}/5 Google Maps Link = {{ $json.google_maps_url }} 👉 Result: The data is now clean and ready for Airtable. Step 5 – Airtable Storage Node**: Airtable → Create Record Parameters**: Credential to connect with: Airtable Personal Access Token account Resource: Record Operation: Create Base: Select from list → your base (example: GOOGLE MAPS SCRAPT) Table: Select from list → your table (example: Google maps scrapt) Mapping Column Mode: Map Each Column Manually 👉 To get your Base ID and Table ID, open your Airtable in the browser: https://airtable.com/appA6eMHOoquiTCeO/tblZFszM5ubwwSYDK Here: Base ID = appA6eMHOoquiTCeO Table ID = tblZFszM5ubwwSYDK Authentication Go to: https://airtable.com/create/tokens Create a new Personal Access Token Give it access to the correct base Copy the token into n8n credentials (select Airtable Personal Access Token). Field Mapping (example) Company: {{ $json['Company'] }} Email: {{ $json.Email }} Phone: {{ $json['Phone'] }} Website: {{ $json['Website'] }} LinkedIn: {{ $json.LinkedIn }} Facebook: {{ $json.Facebook }} City: {{ $json.City }} Category: {{ $json['Category'] }} Google Maps Reviews: {{ $json['Google Maps Reviews'] }} Google Maps Link: {{ $json['Google Maps Link'] }} 👉 Result: Each lead scraped from Google Maps is automatically saved into Airtable, ready to be filtered, sorted, or used for outreach. Step 6 – Automatic Email Node**: Gmail → Send Email Parameters**: To: = {{ $json.fields.Email }} Subject: = {{ $json.fields['Company'] }} Message: HTML email with dynamic lead details. Example HTML message: Hello {{ $json.fields['Company'] }} team, I design custom automations for training centers. Goal: zero repetitive manual tasks, from registration to invoicing. Details: {{ $json.fields['Company'] }} in {{ $json.fields.City }} — website: {{ $json.fields['Website'] }} — {{ $json.fields['Google Maps Reviews'] }} Interested in a quick 15-min call to see a live demo? 👉 Result: Each contact receives a fully personalized email with their company name, city, website, and Google Maps rating. Final Result With just one click: Scrape Google Maps (Apify). Clean and structure the data (Set). Save everything into Airtable. Send personalized emails via Gmail. 👉 All without copy-paste, without CSV, and without Excel headaches.

Who’s it for This template is perfect for marketers, sales teams, and entrepreneurs who need verified business leads without spending hours on manual research. If you’re running outreach campaigns, selling B2B services, or building prospect databases, this workflow saves you time and ensures your lead list is always fresh. How it works Start with a Google Maps search for a chosen business type and location (e.g., “Call centers in New York”). The workflow scrapes raw data, extracting business names, phone numbers, addresses, websites, and emails. Using regex logic, it filters and cleans data, ensuring valid contact details. Finally, it exports all leads into Google Sheets, giving you a ready-to-use contact list for outreach or CRM import. How to set up Replace the placeholder values in the Set Form Fields node with your target industry and location. Connect your Google Sheets account and provide the sheet ID. Run the workflow to start building your lead list. Requirements Google Sheets credentials Business type + location input How to customize the workflow Change the max_results field to control the number of businesses scraped. Add extra regex filters to capture more fields (e.g., social links). Integrate with your CRM or email platform to send leads directly to your outreach pipeline.

Overview When designing user interfaces, toolbar icons often get overlooked, even though their placement and grouping dramatically impact usability and user flow. This workflow leverages Gemini AI to automatically analyze UI screens, classify toolbar icons based on Apple’s Human Interface Guidelines (HIG), and suggest optimal placements. By combining AI analysis with structured placement logic, this workflow helps designers build more consistent, efficient, and user-friendly interfaces—without spending hours manually arranging icons. 🚀 Features AI Classification**: Uses Gemini AI to analyze screenshots and classify icons into roles like .primaryAction, .navigation, .confirmationAction, and more. HIG-Based Placement**: Automatically assigns icons to the correct toolbar areas—Leading (Left), Trailing (Right), Center, Bottom, or System-decided. Usage-Aware Reordering**: Reorders icons based on frequency of use so the most relevant actions appear where users expect them. JSON Output**: Delivers structured results for seamless integration into design tools or documentation. 🔧 Setup Instructions Install the Workflow: Import the workflow into your n8n instance. Configure Input: Upload a screenshot of your UI. Upload a set of icons you want to classify and place. Set Up Gemini AI Node: Add your Gemini AI API key in the node’s credentials. Run the Workflow: Submit the inputs and let the AI classify and assign placements. Export Results: Copy the JSON output or connect the workflow to your preferred design/documentation tools. ⚙️ How It Works Form Submission – Capture screenshot + icons. Gemini AI Agent – Interprets screen context and classifies each icon. Placement Logic – Maps icons to the correct toolbar areas. Reordering – Adjusts order based on relevance and HIG standards. Structured Output – Produces clean JSON for further use. 🎨 Customization Change AI Prompts**: Modify the Gemini AI node prompts to reflect your app’s design language. Adjust Placement Rules**: Update logic to follow custom guidelines beyond Apple HIG. Integrate with Design Tools**: Send the JSON output directly to tools like Figma, Sketch, or internal systems. 💡 Why This Matters Consistency**: Ensures toolbar designs always follow Apple’s HIG. Efficiency**: Saves designers hours of manual icon placement. Scalability**: Works across multiple screens, flows, and apps. AI-Assisted Design**: Augments designer decisions with structured insights instead of replacing them.

Who's it for This template is perfect for business owners, developers, and marketers who want to add a professional, branded AI chatbot to their website. Whether you're running an e-commerce site, a SaaS platform, or a corporate website, this template gives you a fully customizable chat widget that integrates seamlessly with your brand. How it works The template creates a webhook endpoint that receives chat messages and processes them through an AI agent powered by DeepSeek. The workflow includes: Webhook endpoint** that accepts POST requests from your website AI Agent** that processes user messages and maintains conversation context Memory buffer** that remembers conversation history for each user session Response formatting** that sends AI replies back to your chat widget The chat widget itself is a vanilla JavaScript component that you embed on your website. It features: Customizable colors, branding, and positioning Light/dark theme support Mobile-responsive design Local conversation history Session management with expiration WordPress plugin integration How to set up Import the workflow into your n8n instance Configure your DeepSeek API credentials in the DeepSeek Chat Model node Activate the workflow to generate your webhook URL Copy the webhook URL from the Webhook node Embed the chat widget on your website using the provided JavaScript files Requirements n8n instance** (self-hosted or cloud) DeepSeek API account** and API key Website** where you want to embed the chatbot Basic HTML/JavaScript knowledge** for customization How to customize the workflow AI Agent Configuration Modify the AI Agent prompt to change how the bot responds Adjust the memory buffer settings for conversation context Change the AI model parameters for different response styles Webhook Customization Add authentication headers if needed Modify the response format to match your requirements Add additional processing nodes before the AI Agent Chat Widget Styling Change brandColor and accentColor to match your brand Customize the bot name, avatar, and welcome message Adjust positioning and launcher style Enable dark mode or HTML responses as needed Advanced Features Add user authentication integration Implement rate limiting Connect to your CRM or support system Add analytics and tracking Template Features ✅ No hardcoded API keys - uses n8n credential system ✅ Sticky notes included - explains the entire workflow ✅ Professional branding - fully customizable appearance ✅ WordPress ready - includes plugin and shortcode support ✅ Mobile responsive - works on all devices ✅ Session management - remembers conversations per user Use Cases Customer Support**: Provide instant AI-powered assistance Lead Generation**: Engage visitors and collect contact information Product Guidance**: Help customers find the right products/services FAQ Automation**: Answer common questions automatically Booking Assistant**: Help with appointments and reservations E-commerce Support**: Guide customers through purchases Technical Details The workflow uses the LangChain AI Agent with DeepSeek as the language model and includes a Memory Buffer for conversation context. The webhook response format is optimized for the chat widget. Live Demo Try it online: Live Demo Experience the chatbox widget in action with a working n8n webhook integration. The demo showcases all features including light/dark themes, HTML responses, and session management. Note: This template includes a complete JavaScript chat widget and WordPress plugin, making it ready for immediate use on any website. The workflow is designed to be production-ready with proper error handling and security considerations.

This n8n workflow automates the entire content creation and publishing pipeline for engaging, AI-generated visual stories, ensuring image and video quality with human-in-the-loop approvals. What it does: It takes a narrative concept (e.g., 'A Day in the Life of a Serene Skeleton') and transforms it into a series of unique images and videos, which are then published across multiple social media platforms. How it works: Creative Conceptualization: An AI 'Creative Director' develops a detailed narrative, including scenes, moods, and character details. Prompt Engineering: An AI 'Creative Technician' translates the narrative into precise text-to-image and text-to-video prompts, maintaining a consistent artistic style, lighting, and character appearance. AI Asset Generation: Replicate's AI models (Qwen-Image for images and Seedance-1-Lite for videos) create the visual content from these prompts. Human-in-the-Loop Approval: Generated images and videos are sent to Slack for manual review. Users can approve or request regeneration, ensuring creative control and quality. Multi-Platform Publishing: Approved content is automatically published via Blotato to Instagram and Facebook (videos), and TikTok (image slideshows), ready for your audience. Technical Requirements: Replicate Account with Balance: For image and video generation (using Qwen-Image and Seedance-1-Lite). Blotato Subscription: For seamless publishing to multiple social media platforms. OpenRouter Account with Balance: To access various Large Language Models (LLMs) like Gemini 2.5 Flash for creative direction and prompt generation. Slack Account: For the human-in-the-loop approval process. Customization Potential: This workflow serves as a robust foundation that can be easily adapted for various use cases beyond story narratives, such as: Automating product publishing with AI-generated visuals and descriptions. Creating dynamic advertising content for campaigns. Generating personalized visual content for marketing. Scaling content creation for personal or e-commerce brands. Why use it? Ideal for content creators, marketers, and businesses seeking to scale their visual content production, maintain creative control through human oversight, and automate distribution (with scheduling option) to key social media channels (Instagram, Facebook, TikTok, X, Pinterest, YouTube, and more). Customize the initial story brief to unleash endless themed narratives tailored to your brand.

Author: Jadai Kongolo Overview This comprehensive n8n workflow automates the entire production pipeline for creating viral "versus" style battle videos. The system generates dramatic AI-powered fight scenes between animals (or any characters you choose), complete with photorealistic imagery, cinematic effects, and automatic multi-platform publishing. Perfect for content creators looking to generate engaging short-form content at scale without manual editing or design work. Use Cases Viral Social Media Content: Automatically produce trending "X vs Y" battle videos that perform exceptionally well on TikTok, Instagram Reels, and YouTube Shorts. These comparison-style videos consistently generate high engagement and shares. Educational Entertainment: Create visually stunning educational content comparing animals, historical figures, sports teams, or any competitive matchups while maintaining viewer interest through dramatic AI-generated imagery. Automated Content Pipeline: Build a hands-free content factory that can produce multiple videos per day on schedule, complete with automatic posting to all major social platforms through integrated social media management tools. 👉 check out the UGC version of this here How It Works Stage 1 - Scene Generation The workflow begins by fetching a main character from your Google Sheets database (filtered by "To Do" status). An AI agent powered by GPT-4.1-mini then generates eight unique opponents from your specified category, ensuring each comes from a different environment or background for maximum variety and interest. Stage 2 - AI Image Creation The system creates three distinct types of images for each matchup: Close-Up Portraits: Generates fierce, intimidating close-up shots of both the main character and each opponent using Flux image generation through PiAPI. The AI creates hyper-realistic, photorealistic images showing each character roaring with detailed textures, dramatic lighting, and threatening expressions. Battle Aftermath Scenes: A separate AI agent determines the realistic winner based on each character's strengths, then generates a dramatic full-body scene showing the victor standing dominantly over the defeated opponent. These images include visible battle scars, wounds, and cinematic composition that makes the outcome unmistakably clear. The workflow includes intelligent polling mechanisms (90-second waits) to ensure all images are fully generated before proceeding, then aggregates and stores all image URLs in your Google Sheet for reference. Stage 3 - Video Assembly Using Creatomate's video rendering API, the workflow combines all generated images with background music and animated transitions into a polished final video. The template creates a fast-paced montage showing all eight battles with "VS" graphics and dynamic cuts timed to music beats. Stage 4 - Multi-Platform Publishing Once rendered, the video is automatically uploaded to Blotato's social media management platform and simultaneously published to: Instagram Reels** with optimized captions TikTok** with proper AI-generated content disclosure YouTube Shorts** as unlisted for review The workflow updates your Google Sheet with "Created" status and final video URL for tracking and analytics. Customization Options Content Themes Modify the Google Sheet to change from animals to any category: superheroes, historical warriors, vehicles, mythical creatures, sports teams, etc. Adjust AI prompts in the "Scene Creator" node to control opponent selection criteria Edit the "Image Prompt Generator" to customize visual style (fantasy, sci-fi, realistic, cartoon, etc.) Video Production Change video dimensions in "Generate Close Ups" and "Generate Scene" nodes for different platform requirements Replace the Creatomate template with your own design for different visual styles Swap background music by updating the music source URL in the "Render Video" node Adjust the number of battles per video (currently 8 scenes) Publishing Settings Configure posting schedules via the Schedule Trigger node Modify platform-specific settings (privacy levels, comments, duets) in Instagram/TikTok/YouTube nodes Add or remove social platforms by connecting additional Blotato API endpoints Customize captions using data from your Google Sheet AI Models Switch between different OpenRouter models for cost/quality tradeoffs Use GPT-4.1 for complex winner determination and GPT-4.1-mini for faster scene generation Experiment with different Flux models through PiAPI for various artistic styles Prerequisites Google Sheets**: Connected Google account with access to the workflow template OpenRouter API**: For GPT-4.1 and GPT-4.1-mini access PiAPI Account**: For Flux image generation (use referral code for bonus credits) Creatomate Account**: For video rendering with template access Blotato Account**: For multi-platform social media publishing (use promo code "NATE30" for 30% off for 6 months) 🛠️ Setup Guide Make a copy of this Google Sheet Template and connect it to the five Google Sheet nodes in the workflow: Get Main Character Add Close Ups Add Winner Get Elements Update Video Status Connect your OpenRouter API key to the two OpenRouter nodes in the "Output Parser & Chat Models" section: GPT 4.1-mini GPT 4.1 Create a PiAPI account and connect your API key to: Generate Close Ups Generate Scene Get Close Ups Get Winners Create a Creatomate account and connect your template ID and API key to the Render Video node. You can duplicate the same template shown in the video by using the source code linked in the same Skool post where you downloaded the workflow. Connect your Blotato account and get your API key to enable auto-publishing: Configure the Upload to Blotato node Add your account IDs to Instagram, TikTok, and YouTube nodes Customize the Schedule Trigger node to set your desired posting frequency (daily, weekly, etc.) The Generate authentic, influencer-style UGC videos on autopilot version of this AI video generator can be found here.

Try It Out! This n8n template helps you analyze Google Maps reviews for a list of restaurants, summarize them with AI, and identify optimization opportunities—all in one automated workflow. Whether you're managing multiple locations, helping local restaurants improve their digital presence, or conducting a competitor analysis, this workflow helps you extract insights from dozens of reviews in minutes. How It Works? Start with a pre-filled list of restaurants in Google Sheets. The workflow uses SerpAPI to scrape Google Maps reviews for each listing. Reviews with content are passed to ChatGPT for summarization. Empty or failed reviews are logged in a separate tab for easy follow-up. Results are stored back in your Google Sheet for analysis or sharing How To Use Customize the input list in Google Sheets with your own restaurants. Update the OpenAI prompt if you want a different style of summary. You can trigger this manually or swap in a schedule, webhook, or other event. Requirements A SerpAPI account to fetch reviews An OpenAI account for ChatGPT summarization Access to Google Sheets and n8n Who Is It For? This is helpful for people looking to analyze a large batch of Google reviews in a short amount of time. Additionally, it can be used to compare restaurants and see where each can be optimized. How To Set-Up? Use a SerpAPI endpoint to include in the HTTP request node. Refer to this n8n documentation for more help! https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolserpapi/. Happy Automating!

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Complete MCP server exposing 27 Amazon CloudWatch Application Insights API operations to AI agents. ⚡ 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 Credentials Add Amazon CloudWatch Application Insights credentials 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 This workflow converts the Amazon CloudWatch Application Insights API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to http://applicationinsights.{region}.amazonaws.com • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (27 total) 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Createapplication (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.CreateApplication: Adds an application that is created from a resource group. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Createcomponent (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.CreateComponent: Creates a custom component by grouping similar standalone instances to monitor. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Createlogpattern (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.CreateLogPattern: Adds an log pattern to a LogPatternSet. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Deleteapplication (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DeleteApplication: Removes the specified application from monitoring. Does not delete the application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Deletecomponent (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DeleteComponent: Ungroups a custom component. When you ungroup custom components, all applicable monitors that are set up for the component are removed and the instances revert to their standalone status. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Deletelogpattern (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DeleteLogPattern: Removes the specified log pattern from a LogPatternSet. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describeapplication (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeApplication: Describes the application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describecomponent (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeComponent: Describes a component and lists the resources that are grouped together in a component. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describecomponentconfiguration (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeComponentConfiguration: Describes the monitoring configuration of the component. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describecomponentconfigurationrecommendation (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeComponentConfigurationRecommendation: Describes the recommended monitoring configuration of the component. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describelogpattern (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeLogPattern: Describe a specific log pattern from a LogPatternSet. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describeobservation (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeObservation: Describes an anomaly or error with the application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describeproblem (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeProblem: Describes an application problem. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Describeproblemobservations (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.DescribeProblemObservations: Describes the anomalies or errors associated with the problem. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Listapplications (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.ListApplications: Lists the IDs of the applications that you are monitoring. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Listcomponents (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.ListComponents: Lists the auto-grouped, standalone, and custom components of the application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Listconfigurationhistory (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.ListConfigurationHistory: Lists the INFO, WARN, and ERROR events for periodic configuration updates performed by Application Insights. Examples of events represented are: INFO: creating a new alarm or updating an alarm threshold. WARN: alarm not created due to insufficient data points used to predict thresholds. ERROR: alarm not created due to permission errors or exceeding quotas. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Listlogpatternsets (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.ListLogPatternSets: Lists the log pattern sets in the specific application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Listlogpatterns (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.ListLogPatterns: Lists the log patterns in the specific log LogPatternSet. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Listproblems (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.ListProblems: Lists the problems with your application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Listtagsforresource (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.ListTagsForResource: Retrieve a list of the tags (keys and values) that are associated with a specified application. A tag is a label that you optionally define and associate with an application. Each tag consists of a required tag key and an optional associated tag value. A tag key is a general label that acts as a category for more specific tag values. A tag value acts as a descriptor within a tag key. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Tagresource (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.TagResource: Add one or more tags (keys and values) to a specified application. A tag is a label that you optionally define and associate with an application. Tags can help you categorize and manage application in different ways, such as by purpose, owner, environment, or other criteria. Each tag consists of a required tag key and an associated tag value, both of which you define. A tag key is a general label that acts as a category for more specific tag values. A tag value acts as a descriptor within a tag key. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Untagresource (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.UntagResource: Remove one or more tags (keys and values) from a specified application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Updateapplication (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.UpdateApplication: Updates the application. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Updatecomponent (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.UpdateComponent: Updates the custom component name and/or the list of resources that make up the component. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Updatecomponentconfiguration (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.UpdateComponentConfiguration: Updates the monitoring configurations for the component. The configuration input parameter is an escaped JSON of the configuration and should match the schema of what is returned by DescribeComponentConfigurationRecommendation. 🔧 #X-Amz-Target=Ec2Windowsbarleyservice.Updatelogpattern (1 endpoints) • POST /#X-Amz-Target=EC2WindowsBarleyService.UpdateLogPattern: Adds a log pattern to a LogPatternSet. 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Amazon CloudWatch Application Insights API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Nathan is a proof of concept framework for creating a personal assistant who can handle various day to day functions for you.

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