by David Ashby
Complete MCP server exposing all LinkedIn Tool operations to AI agents. Zero configuration needed - all 1 operations pre-built. β‘ 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 π§ How it Works β’ MCP Trigger: Serves as your server endpoint for AI agent requests β’ Tool Nodes: Pre-configured for every LinkedIn Tool operation β’ AI Expressions: Automatically populate parameters via $fromAI() placeholders β’ Native Integration: Uses official n8n LinkedIn Tool tool with full error handling π Available Operations (1 total) Every possible LinkedIn Tool operation is included: π§ Post (1 operations) β’ Create a post π€ AI Integration Parameter Handling: AI agents automatically provide values for: β’ Resource IDs and identifiers β’ Search queries and filters β’ Content and data payloads β’ Configuration options Response Format: Native LinkedIn Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic π‘ Usage Examples Connect this MCP server to any AI agent or workflow: β’ Claude Desktop: Add MCP server URL to configuration β’ Custom AI Apps: Use MCP URL as tool endpoint β’ Other n8n Workflows: Call MCP tools from any workflow β’ API Integration: Direct HTTP calls to MCP endpoints β¨ Benefits β’ Complete Coverage: Every LinkedIn Tool operation available β’ Zero Setup: No parameter mapping or configuration needed β’ AI-Ready: Built-in $fromAI() expressions for all parameters β’ Production Ready: Native n8n error handling and logging β’ Extensible: Easily modify or add custom logic > π Free for community use! Ready to deploy in under 2 minutes.
by Usman Liaqat
Description: This n8n workflow helps you capture Slack messages via a webhook and download attached media files (like images, documents, or videos) directly from those messages. How it works: Slack Trigger (Webhook) β Listens for new messages in a Slack channel where the app is added. HTTP Request β Uses the file's private download URL to retrieve the media securely. Use cases: Download files shared by team members in a Slack channel. Capture and process media from specific project or support channels. Prepare media for later processing, archiving, or review. Requirements: Slack app with appropriate permissions (files:read, channels:history, etc.). Slack webhook set up to listen to channel messages. - Authenticated HTTP request to handle private Slack file URLs. This template is ideal for users who want full control over file handling triggered by real-time Slack messages.
by Fabrizio Terzi
AI-Driven Handbook Generator with Multi-Agent Orchestration (Pyragogy AI Village) This n8n workflow is a modular, multi-agent AI orchestration system designed for the collaborative generation of Markdown-based handbooks. Inspired by peer learning and open publishing workflows, it simulates a content pipeline where specialized AI agents act in defined roles, enabling true AIβhuman co-creation and iterative refinement. This project is a core component of Pyragogy, an open framework dedicated to ethical cognitive co-creation, peer AIβhuman learning, and human-in-the-loop automation for open knowledge systems. It implements the master orchestration architecture for the Pyragogy AI Village, managing a complex sequence of AI agents to process input, perform review, synthesis, and archiving, with a crucial human oversight step for final approval. How It Works: A Deep Dive into the Workflow's Architecture The workflow orchestrates a sophisticated content generation and review process, ideal for creating AI-driven knowledge bases or handbooks with human oversight. Webhook Trigger & Input:* The process begins when the workflow receives a JSON input via a *Webhook** (specifically at /webhook/pyragogy/process). This input typically includes details like the handbook's title, initial text, and relevant tags. Database Verification:* It first verifies the connection to a *PostgreSQL database** to ensure data persistence. Meta-Orchestrator:* A powerful *Meta-Orchestrator** (powered by gpt-4o from OpenAI) analyzes the initial request. Its role is to dynamically determine and activate the optimal sequence of specialized AI agents required to fulfill the input, ensuring tasks are dynamically routed and assigned based on each agentβs responsibility. Agent Execution & Iteration:** Each activated agent executes its step using OpenAI or custom endpoints. This involves: Content Generation: Agents like the Summarizer and the Synthesizer generate new content or refine existing text. Peer Review Board: A crucial aspect is the Peer Review Board, comprised of AI agents like the Peer Reviewer, the Sensemaking Agent, and the Prompt Engineer. This board evaluates the output for quality, coherence, and accuracy. Reprocessing & Redrafting: If the review agents flag a major_issue, they trigger redrafting loops by generating specific feedback for the Synthesizer. This mechanism ensures iterative refinement until the content meets the required standards. Human-in-the-Loop (HITL) Review:* For final approval, particularly for the Archivist agent's output, a *human review process* is initiated. An email is sent to a human reviewer, prompting them to approve, reject, or comment via a "Wait for Webhook" node. This ensures *human oversight** and quality control. Content Persistence & Versioning:** If the content is approved by the human reviewer: It's saved to a PostgreSQL database (specifically to the handbook_entries and agent_contributions tables). Optionally, the content can be committed to a GitHub repository for version control, provided the necessary environment variables are configured. Notifications:* The final output and the sequence of executed agents can be sent as a notification to *Slack**, if configured. Observe the dynamic loop: orchestrate β assign β generate β review (AI/human) β store Included AI Agents This workflow leverages a suite of specialized AI agents, each with a distinct role in the content pipeline: Meta-Orchestrator:** Determines the optimal sequence of agents to execute based on the input. Summarizer Agent:** Summarizes text into key points (e.g., 3 key points). Synthesizer Agent:** Synthesizes new text and effectively incorporates reprocessing feedback from review agents. Peer Reviewer Agent:** Reviews generated text, highlighting strengths, weaknesses, and suggestions, and indicates major_issue flags. Sensemaking Agent:** Analyzes input within existing context, identifying patterns, gaps, and areas for improvement. Prompt Engineer Agent:** Refines or generates prompts for subsequent agents, optimizing their output. Onboarding/Explainer Agent:** Provides explanations of the process or offers guidance to users. Archivist Agent:** Prepares content for the handbook, manages the human review process, and handles archiving to the database and GitHub. Setup Steps & Prerequisites To get this powerful workflow up and running, follow these steps: Import the Workflow: Import the pyragogy_master_workflow.json (or generate-collaborative-handbooks-with-gpt4o-multi-agent-orchestration-human-review.json) into your n8n instance. Connect Credentials: Postgres: Set up a Postgres Pyragogy DB credential (ID: pyragogy-postgres). OpenAI: Configure an OpenAI Pyragogy credential (ID: pyragogy-openai) for all OpenAI agents. GPT-4o is highly suggested for optimal performance. Email Send: Set up a configured email credential (e.g., for sending human review requests). Define Environment Variables: Define essential environment variables (an .env.template is included in the repository). These include: API base for OpenAI. Database connection details. (Optional) GitHub: For content persistence and versioning, configure GITHUB_ACCESS_TOKEN, GITHUB_REPOSITORY_OWNER, and GITHUB_REPOSITORY_NAME. (Optional) Slack: For notifications, configure SLACK_WEBHOOK_URL. Send a sample payload to your webhook URL (/webhook/pyragogy/process): { "title": "History of Peer Learning", "text": "Peer learning is an educational approach where students learn from and with each other...", "tags": ["education", "pedagogy"], "requireHitl": true } Ideal For This workflow is perfectly suited for: Educators and researchers exploring AI-assisted publishing and co-authoring with AI. Knowledge teams looking to automate content pipelines for internal or external documentation. Anyone building collaborative Markdown-driven tools or AI-powered knowledge bases. Documentation & Contributions: An Open Source and Collaborative Project This workflow is an open-source project and community-driven. Its development is transparent and open to everyone. We warmly invite you to: Review it:** Contribute your analysis, identify potential improvements, or report issues. Remix it:** Adapt it to your specific needs, integrate new features, or modify it for a different use case. Improve it:** Propose and implement changes that enhance its efficiency, robustness, or capabilities. Share it back:** Return your contributions to the community, either through pull requests or by sharing your implementations. Every contribution is welcome and valued! All relevant information for verification, improvement, and collaboration can be found in the official repository: π GitHub β pyragogy-handbook-n8n-workflow
by JPres
π₯ Who Is This For? Content creators, marketing teams, and channel managers who need to streamline video publishing with optimized metadata and scheduled releases across multiple videos. π What Problem Does This Solve? Manual YouTube video publishing is time-consuming and often results in inconsistent descriptions, tags, and scheduling. This workflow fully automates: Extracting video transcripts via Apify for metadata generation Creating SEO-optimized descriptions and tags for each video Setting videos to private during initial upload (critical for scheduling) Implementing scheduled publishing at strategic times Maintaining consistent branding and formatting across all content π Node-by-Node Breakdown | Step | Node Purpose | |------|--------------| | 1 | Every Day (Scheduler) | Trigger workflow on a regular schedule | | 2 | Get Videos to Harmonize | Retrieve videos requiring metadata enhancement | | 3 | Get Video IDs (Unpublished) | Filter for videos that need publishing | | 4 | Loop over Video IDs | Process each video individually | | 5 | Get Video Data | Retrieve metadata for the current video | | 6 | Loop over Videos with Parameter IS | Set parameters for processing | | 7 | Set Videos to Private | Ensure videos are private (required for scheduling) | | 8 | Apify: Get Transcript | Extract video transcript via Apify | | 9 | Fetch Latest Videos | Get most recent channel content | | 10 | Loop Over Items | Process each video item | | 11 | Generate Description, Tags, etc. | Create optimized metadata from transcript | | 12 | AP Clean ID | Format identifiers | | 13 | Retrieve Generated Data | Collect the enhanced metadata | | 14 | Adjust Transcript Format | Format transcript for better processing | | 15 | Update Video's Metadata | Apply generated description and tags to video | βοΈ Pre-conditions / Requirements n8n with YouTube API credentials configured Apify account with API access for transcript extraction YouTube channel with upload permissions Master templates for description formatting Videos must be initially set to private for scheduling to work βοΈ Setup Instructions Import this workflow into your n8n instance. Configure YouTube API credentials with proper channel access. Set up Apify integration with appropriate actor for transcript extraction. Define scheduling parameters in the Every Day node. Configure description templates with placeholders for dynamic content. Set default tags and customize tag generation rules. Test with a single video before batch processing. π¨ How to Customize Adjust prompt templates for description generation to match your brand voice. Modify tag selection algorithms based on your channel's SEO strategy. Create multiple publishing schedules for different content categories. Integrate with analytics tools to optimize publishing times. Add notification nodes to alert when videos are successfully scheduled. β οΈ Important Notes Videos MUST be uploaded as private initially - the Publish At logic only works for private videos that haven't been published before. Publishing schedules require videos to remain private until their scheduled time. Transcript quality affects metadata generation results. Consider YouTube API quotas when scheduling large batches of videos. π Security and Privacy API credentials are stored securely within n8n. Transcripts are processed temporarily and not stored permanently. Webhook URLs should be protected to prevent unauthorized triggering. Access to the workflow should be limited to authorized team members only.
by Incrementors
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. π¦ Multi-Platform Price Finder: Scraping Prices with Bright Data & Telegram An intelligent n8n automation that fetches real-time product prices from marketplaces like Amazon, Wayfair, Lowe's, and more using Bright Data's dataset, and sends promotional messages via Telegram using AIβperfect for price tracking, deal alerts, and affiliate monetization. π Overview This automation tracks product prices across top e-commerce platforms using Bright Data and sends out alerts via Telegram based on the best available deals. The workflow is designed for affiliate marketers, resellers, and deal-hunting platforms who want real-time competitive pricing. β¨ Key Features π Multi-Platform Scraping: Supports Amazon, Wayfair, Lowe's, and more β‘ Bright Data Integration: Access to structured product snapshots π’ AI-Powered Alerts: Generates Telegram-ready promo messages using AI π§ Lowest Price Logic: Filters and compares products across sources π Data Merge & Processing: Combines multiple sources into a single stream π Keyword-Driven Search: Searches using dynamic keywords from form input π¦ Scalable Design: Built for multiple platform processing simultaneously π§Ό Clean Output: Strips unnecessary formatting before publishing π― What This Workflow Does Input Search Keywords**: User-defined keyword(s) from a form trigger Platform Sources**: Wayfair, Lowe's, Amazon, etc. Bright Data API Key**: Needed for authenticated scraping Processing Steps User Input via n8n form trigger (keyword-based) Bright Data API Trigger for each marketplace Status Polling: Wait until scraping snapshot is ready Data Retrieval: Fetches JSON results from Bright Data snapshot Data Cleaning & Normalization: Price, title, and URL are extracted Merging Products from all platforms Find Lowest Price Product using custom JS logic AI Prompt Generation via Claude/Anthropic Telegram Formatting and alert message creation Output ποΈ Product Title π° Final Price π Product URL βοΈ Promotional Message (for Telegram/notifications) π Setup Instructions Step 1: Import Workflow Open n8n > Workflows > + Add Workflow Import the provided JSON file Step 2: Configure Bright Data Add credentials under Credentials β Bright Data API Set the appropriate dataset_id for each platform Ensure dataset includes title, price, and url fields Step 3: Enable Keyword Trigger Use the built-in Form Trigger node Input: Single keyword field (SearchHere) Step 4: Telegram or AI Integration Modify prompt node for your language or tone Add Telegram webhook or integration where needed π Usage Guide Adding Keywords Trigger the form with a product keyword like iPhone 15 Wait for workflow to fetch best deals and generate Telegram message Understanding AI-Powered Output AI creates a short, engaging message like: > "π₯ Deal Alert: Get the iPhone 15 for just βΉ74,999! Limited stockβCheck it out: [link]" Debugging Output Output node shows cleaned JSON with title, price, url, and message If no valid results, debug message is returned with sample structure info π§ Customization Options Add More Marketplaces Clone any HTTP Request node (e.g., for Wayfair) Update dataset_id and required output fields Modify Price Logic Update the Code1 node to change comparison (e.g., highest price instead of lowest) Change Message Format Edit the AI Agent prompt to customize tone/language Add emoji, CTAs, or markdown formatting as needed π§ͺ Test & Activation Add a few sample keywords via form trigger Run manually or set as a webhook for external app input Check final AI-generated message in output node π¨ Troubleshooting | Issue | Solution | |-------|----------| | No Data Returned | Ensure keyword matches real products | | Status Not 'Ready' | Bright Data delay; add Wait nodes | | Invalid API Key | Check Bright Data credentials | | AI Errors | Adjust prompt or validate input fields | π Use Cases π° Affiliate Campaigns: Show best deals across platforms π Deal Pages: Post live offers with product links π§ Competitor Analysis: Track cross-platform pricing π Alert Bots: Send real-time alerts to Telegram or Slack β Quick Setup Checklist [x] Bright Data API credentials configured [x] n8n form trigger enabled [x] Claude or AI model connected [x] All HTTP requests working [x] AI message formatting verified π Example Output { "title": "Apple iPhone 15 Pro Max", "price": 1199, "url": "https://amazon.com/iphone-15", "message": "π₯ Grab the Apple iPhone 15 Pro Max for just $1199! Limited dealβCheck it out: https://amazon.com/iphone-15" } π¬For any questions or support, please contact: π§ <info@incrementors.com> or fill out this form: https://www.incrementors.com/contact-us/
by David Ashby
π οΈ Pushover Tool MCP Server Complete MCP server exposing all Pushover Tool operations to AI agents. Zero configuration needed - 1 operation pre-built. β‘ 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 π§ How it Works β’ MCP Trigger: Serves as your server endpoint for AI agent requests β’ Tool Nodes: Pre-configured for every Pushover Tool operation β’ AI Expressions: Automatically populate parameters via $fromAI() placeholders β’ Native Integration: Uses official n8n Pushover Tool tool with full error handling π Available Operations (1 total) Every possible Pushover Tool operation is included: π¬ Message (1 operations) β’ Push a message π€ AI Integration Parameter Handling: AI agents automatically provide values for: β’ Resource IDs and identifiers β’ Search queries and filters β’ Content and data payloads β’ Configuration options Response Format: Native Pushover Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic π‘ Usage Examples Connect this MCP server to any AI agent or workflow: β’ Claude Desktop: Add MCP server URL to configuration β’ Custom AI Apps: Use MCP URL as tool endpoint β’ Other n8n Workflows: Call MCP tools from any workflow β’ API Integration: Direct HTTP calls to MCP endpoints β¨ Benefits β’ Complete Coverage: Every Pushover Tool operation available β’ Zero Setup: No parameter mapping or configuration needed β’ AI-Ready: Built-in $fromAI() expressions for all parameters β’ Production Ready: Native n8n error handling and logging β’ Extensible: Easily modify or add custom logic > π Free for community use! Ready to deploy in under 2 minutes.
by Matthieu
LinkedIn Profile Tracker Automation Who is this for? This template is ideal for sales teams, recruiters, business development professionals, and relationship managers who need to monitor changes in their network's LinkedIn profiles. Perfect for agencies tracking client personnel changes, HR teams monitoring talent movements, sales professionals staying updated on prospect job changes, and content teams tracking influencer activity. What problem does this workflow solve? Manually checking LinkedIn profiles for updates like job changes, status modifications, profile edits, or latest posts is extremely time-consuming and easy to miss. This automation eliminates the need for constant manual monitoring while ensuring you never miss important changes that could signal new business opportunities, relationship updates, or content engagement opportunities. What this workflow does This workflow automatically monitors a list of LinkedIn profiles on a weekly schedule, detects any changes in: Personal information** (name, headline, summary) Job status** (hiring/open to work flags) Latest work experience** (new positions, company changes) Recent posts** (latest content activity) When changes are detected, it immediately sends Slack notifications with before/after comparisons and updates your tracking database to maintain historical records of all profile evolution. Setup Create a Ghost Genius API account and get your API key for LinkedIn profile scraping Configure HTTP Request nodes with Header Auth credentials using your Ghost Genius API key Set up your Google Sheets database with columns: Firstname, Lastname, LinkedIn URL, ID Tagline, Summary, Latest experience Open to work?, Hiring?, Latest post Configure Slack webhook integration for real-time notifications Set up credentials for Google Sheets and Slack following n8n documentation Add LinkedIn profile URLs to your Google Sheet to start monitoring How to customize this workflow Modify the schedule trigger** to check profiles daily, bi-weekly, or monthly based on your monitoring needs Customize Slack notification messages** to include additional context, mentions, or custom formatting Add email notifications** alongside Slack alerts for critical changes like job transitions Set up filtered notifications** to only alert on specific types of changes (e.g., job changes only, posts from key influencers) Add post content analysis** to detect mentions of your company or competitors Integrate with CRM systems** to automatically update lead records when profile changes occur
by Angel Menendez
Submission Overview for Voiceflow Demo Workflow View the YouTube video for this workflow here. Who is this for? This workflow is ideal for businesses and developers using Voiceflow to power AI voice chatbots. It benefits teams that want to enhance chatbot functionality through integrations with platforms like Zendesk, Google Calendar, and Airtable. What problem is this workflow solving? The workflow addresses the need for seamless integration of chatbot interactions with backend systems. It automates customer service tasks such as ticket creation, meeting scheduling, and data reporting, reducing manual effort and enhancing efficiency. What does this workflow do? Customer Lookup:** Checks the database for existing customers and returns relevant details or a "NOT_FOUND" status. Zendesk Ticket Creation:** Automates the creation of support tickets for customer issues. Meeting Scheduling:** Integrates with Google Calendar to provide availability and schedule meetings. Transcript Reporting:** Aggregates interaction data and sends it to Airtable for analysis by the product team. Setup Configure your Voiceflow chatbot to connect to this workflow via a webhook. Set up the required integrations: Zendesk API: For ticket creation. Google Calendar API: For scheduling. Airtable API: For storing transcripts. Customize the workflow's nodes to match your use case, such as database fields or API endpoints. Deploy the workflow on your n8n instance and test the integrations. How to customize this workflow to your needs Adjust database queries to match your customer data schema. Modify the Zendesk ticket payload to include additional fields or custom formats. Update Google Calendar configurations for different scheduling requirements. Add or remove Airtable fields based on the product team's analysis needs. This template adheres to n8nβs submission guidelines, ensuring clarity, relevance, and broad applicability for users in customer service, product development, and automation.
by Amjid Ali
Overview This workflow template automates lead management and customer inquiry processing by integrating ERPNext, AI agents, and email notifications. It streamlines the process of capturing leads, analyzing inquiries, and generating actionable responses. The workflow uses ERPNext to capture inquiries, analyzes them with AI, and notifies the appropriate team or individual, all while maintaining a professional approach. What This Template Does ERPNext Webhook Integration: Captures leads and inquiries through ERPNext webhooks. Triggers the workflow when a new lead is created. AI-Powered Inquiry Analysis: Uses AI to extract key details from lead notes (e.g., customer name, organization, inquiry summary). Classifies inquiries as valid or invalid based on relevance to products, services, or solutions. Contact Assignment: Matches inquiries to the appropriate contact(s) using a Google Sheets database or ERPNext contact information. Handles multiple contacts if required. Email Notifications: Generates professional email notifications for valid inquiries. Sends emails to the appropriate contact(s) with inquiry details and action steps. Invalid Lead Handling: Identifies invalid inquiries (e.g., unrelated to products or services) and flags them for follow-up or dismissal. Custom Email Formatting: Converts plain text into professionally formatted HTML emails. Ensures that communication is clear, concise, and visually appealing. How It Works Step 1: Capture Lead Data Webhook in ERPNext:** Create a webhook in ERPNext for the "Lead" DocType. Set the trigger to on_insert to capture new leads in real-time. Lead Details:** The workflow fetches lead details, including notes, contact information, and the source of the lead. Step 2: Validate and Analyze Inquiry AI Agent for Analysis:** An AI agent analyzes the lead notes to extract key details and classify the inquiry as valid or invalid. The analysis includes checking the relevance of the inquiry to products, services, or solutions offered by the company. Invalid Leads:** If the inquiry is invalid, the workflow flags it and stops further processing. Step 3: Assign Contact(s) Google Sheets Integration:** Uses a Google Sheets database to map products, services, or solutions to responsible contacts. Ensures that inquiries are directed to the right person or team. Multiple Contacts:** Handles cases where multiple contacts are responsible for a particular product or service. Step 4: Generate and Send Email Notifications AI-Generated Emails:** The workflow generates a professional email summarizing the inquiry. Emails include details like customer name, organization, inquiry summary, and action steps. Custom HTML Formatting:** Emails are converted to HTML for a polished and professional appearance. Send Notifications:** Sends email notifications through Microsoft Outlook or another configured email client. Optionally, notifies via WhatsApp or SMS for urgent inquiries. Step 5: Post-Inquiry Actions ERPNext Record Updates:** Updates the lead record in ERPNext with relevant details, including inquiry status and contact information. Setup Instructions Prerequisites ERPNext: A configured ERPNext instance with lead data and a webhook for the "Lead" DocType. Google Sheets: A sheet mapping products, services, or solutions to responsible contacts. AI Integration: Credentials for OpenAI or other supported AI platforms. Email Client: Credentials for Microsoft Outlook or another email client. Step-by-Step Setup ERPNext Configuration: Create a webhook for the "Lead" DocType in ERPNext. Test the webhook with sample data to ensure proper integration. Workflow Import: Import the workflow template into n8n. Configure nodes with your API credentials for ERPNext, Google Sheets, and AI tools. Google Sheets Integration: Prepare a Google Sheet with columns for product, service, or solution and the responsible contact(s). Link the sheet to the workflow. AI Agent Configuration: Customize the AI agentβs prompts to align with your businessβs products and services. Adjust criteria for valid and invalid inquiries as needed. Email Setup: Configure the email client node with your email service credentials. Customize the email template for your organization. Testing: Run the workflow with sample leads to validate the entire process. Check email notifications, contact assignments, and record updates in ERPNext. Dos and Donβts Dos: Test Thoroughly:** Test the workflow with various scenarios before deploying in production. Secure Credentials:** Keep API and email credentials secure to avoid unauthorized access. Customize Prompts:** Tailor AI prompts to match your business needs and language style. Use Professional Email Templates:** Ensure emails are clear and well-formatted. Donβts: Skip Validation:** Always validate inquiry data to avoid sending irrelevant notifications. Overload the Workflow:** Avoid adding unnecessary nodes that can slow down processing. Ignore Errors:** Monitor logs and address errors promptly for a smooth workflow. Resources GET n8n Now N8N COURSE n8n Book YouTube Tutorial:** Watch the full step-by-step tutorial on setting up this workflow: SyncBricks YouTube Channel Courses and Training:** Learn more about ERPNext and AI automation through my comprehensive courses: SyncBricks LMS Support and Contact:** Email: amjid@amjidali.com Website: SyncBricks LinkedIn: Amjid Ali
by Niranjan G
π‘οΈ Automated AWS Key Compromise Remediation Description This n8n workflow provides a secure, enterprise-grade response system for AWS IAM access key compromises with built-in form submission and human approval mechanisms. When an AWS access key is suspected to be compromised, this workflow enables rapid containment through a secure web form interface with basic authentication, human approval via Slack, and automated damage prevention through immediate key deactivation, credential invalidation, and comprehensive security reporting. How This Workflow is Useful Secure Form-Based Response Authenticated Form Submission**: Secure web form with basic authentication for capturing compromise details Human Approval Workflow**: Slack-based approval system for sensitive security operations Rapid Key Deactivation**: Instantly disables compromised access keys after approval Credential Invalidation**: Creates and applies security policies to invalidate existing temporary credentials Policy Analysis**: Automatically scans and analyzes both inline and attached IAM policies for the affected user AI-Powered Reporting**: Generates detailed security reports with intelligent analysis and team notifications Business Value Reduces Mean Time to Response (MTTR)**: Automates manual security procedures that typically take hours Minimizes Security Exposure**: Immediate containment prevents potential data breaches and unauthorized resource access Ensures Compliance**: Provides audit trails and documentation required for security compliance frameworks Cost Prevention**: Prevents potential financial damage from compromised credentials being used maliciously Rapid Response Capability**: Streamlines security response procedures when incidents are detected Technical Benefits AWS Best Practices**: Implements official AWS security recommendations for key compromise response Scalable Architecture**: Handles multiple access keys and complex IAM policy structures Error Handling**: Robust error handling ensures workflow continues even if individual steps fail Audit Trail**: Complete logging of all actions taken during the incident response Integration Ready**: Easily integrates with existing security tools and notification systems Use Cases 1. Incident Response Automation Automated response to security alerts from AWS CloudTrail Integration with SIEM systems for immediate key compromise response 24/7 security monitoring and automated containment 2. Compliance and Audit Meeting regulatory requirements for incident response documentation Providing audit trails for security compliance frameworks (SOC 2, ISO 27001, PCI DSS) Demonstrating due diligence in security incident handling 3. Multi-Account Management Centralized security response across multiple AWS accounts Consistent incident response procedures across different environments Standardized security automation for enterprise AWS deployments 4. Security Training and Testing Security team training on AWS incident response procedures Tabletop exercises and security drills Testing and validation of security response capabilities Key Features Core Functionality β Secure Form Interface: Web form with basic authentication for secure data submission β Human Approval Gate: Slack-based approval workflow for sensitive operations β Authenticated Data Processing: Secure handling of form submissions with validation β Immediate Key Deactivation: Instant disabling of compromised credentials after approval β Security Policy Generation: Automatic creation and attachment of credential invalidation policies β Policy Analysis: Deep analysis of user permissions and attached policies β AI Security Analysis: Intelligent security report generation with risk assessment β Team Notifications: Real-time Slack notifications to security teams β Comprehensive Logging: Complete audit trail of all response actions Technical Specifications Secure Form Interface**: Web form with basic authentication for secure data capture Human Approval System**: Slack-based approval workflow for sensitive operations AWS API Integration**: Direct integration with AWS IAM APIs Authentication Layer**: Basic auth protection for form submissions Error Handling**: Robust error handling with continuation on non-critical failures Scalable Processing**: Handles multiple policies and complex IAM structures Security Best Practices**: No hardcoded credentials, uses AWS credential management Modular Design**: Easy to customize and extend for specific organizational needs Prerequisites Required Credentials AWS Credentials** with IAM permissions for: ListAccessKeys, UpdateAccessKey ListUserPolicies, ListAttachedUserPolicies CreatePolicy, AttachUserPolicy GetPolicy, GetPolicyVersion, GetUserPolicy Required Integrations Slack Workspace** for approval workflow and team notifications Basic Authentication Setup** for secure form access Optional Integrations AI Language Model** (Claude/OpenAI) for intelligent security analysis and report generation Installation and Setup Import the workflow into your n8n instance Configure AWS credentials in n8n credential manager Set up basic authentication for the secure form interface Configure Slack integration for approval notifications and team alerts Set up AI model (optional) for enhanced security analysis and reporting Configure approval workflow in Slack for human oversight Test in development environment before production use Workflow Inputs Secure Form Submission This workflow uses a secure web form with basic authentication to capture compromise details: Username**: The AWS IAM username of the compromised account Access Key ID**: The specific access key ID that has been compromised Authentication & Approval Process Form Authentication: Basic authentication protects the submission form Data Processing: Secure handling and validation of submitted credentials Human Approval: Slack notification sent to security team for approval Automated Execution: Upon approval, the workflow executes the security response This multi-layered approach ensures that sensitive security operations require both authentication and human oversight before execution. π Automate with Slack Integration Want to fully automate and simplify this workflow? Connect it with Slack for seamless team collaboration and instant response capabilities! Interactive Slack Automation Combine this AWS Key Compromise Response workflow with our Interactive Slack Approval & Data Submission System to create a fully automated incident response pipeline: Instant Slack Alerts**: Receive immediate notifications when key compromises are detected One-Click Response**: Trigger the AWS response workflow directly from Slack with interactive buttons Team Collaboration**: Enable security teams to respond collectively through Slack channels Approval Workflows**: Add human approval gates before executing critical security actions Real-time Updates**: Get live status updates and completion notifications in Slack How the Complete Solution Works Detection: External security monitoring tools (CloudTrail, SIEM, etc.) detect potential key compromise Secure Form Access: Security team accesses the authenticated web form to submit compromise details Form Submission: Credentials are securely submitted through the basic auth-protected form Human Approval: Slack notification sent to security team for review and approval Approved Execution: Upon approval, the AWS security response executes automatically Real-time Updates: Progress and completion notifications sent back to Slack Security Analysis: AI-powered analysis and comprehensive reporting delivered to the team Get Started with Full Automation To enable automatic notifications and complete the automation pipeline, use the Interactive Slack Approval & Data Submission System with Webhooks workflow: https://n8n.io/workflows/5049-interactive-slack-approval-and-data-submission-system-with-webhooks/ This integration transforms manual security responses into streamlined, team-collaborative automation that reduces response time from hours to minutes. Security Considerations Form Authentication**: Basic authentication protects the submission interface Human Approval Gate**: Slack-based approval prevents unauthorized execution AWS Credential Management**: Uses AWS credential management best practices No Sensitive Data Storage**: No sensitive data stored in workflow configuration Least-Privilege Access**: Implements least-privilege access principles Complete Audit Trails**: Provides complete audit trails for compliance Secure Data Processing**: Encrypted handling of form submissions and approvals Immediate Damage Prevention**: Designed for rapid containment after approval β οΈ Important Disclaimer Use with Caution: Disabling access keys without proper understanding can significantly impact your personal or business operations. This workflow immediately deactivates AWS access keys, which may disrupt running applications, automated processes, or services that depend on these credentials. AWS Best Practices Recommendation: Use IAM Roles instead of Access Keys** whenever possible for enhanced security IAM roles provide temporary credentials and eliminate the need for long-term access keys Follow the principle of least privilege when assigning permissions Regularly rotate and audit your AWS credentials Implement proper monitoring and alerting for credential usage Before Using This Workflow: Ensure you understand which services and applications use the target access key Have a rollback plan in case of accidental disruption Test in a non-production environment first Coordinate with your team before executing in production For comprehensive AWS security best practices, refer to the AWS Security Best Practices Guide. For more workflows and automation solutions, visit: https://n8n.io/creators/niranjan/
by Alex Kim
Weather via Slack π¦οΈπ¬ Overview This workflow provides real-time weather updates via Slack using a custom Slack command: /weather [cityname] Users can type this command in Slack (e.g., /weather New York), and the workflow will fetch and post the latest forecast, including temperature, wind conditions, and a short weather summary. While this workflow is designed for Slack, users can modify it to send weather updates via email, Discord, Microsoft Teams, or any other communication platform. How It Works Webhook Trigger β The workflow is triggered when a user runs /weather [cityname] in Slack. Geocoding with OpenStreetMap β The city name is converted into latitude and longitude coordinates. Weather Data from NOAA β The coordinates are used to retrieve detailed weather data from the National Weather Service (NWS) API. Formatted Weather Report β The workflow extracts relevant weather details, such as: Temperature (Β°F/Β°C) Wind speed and direction Short forecast summary Slack Notification β The weather forecast is posted back to the Slack channel in a structured format. Requirements A custom Slack app with: The ability to create a Slash Command (/weather) OAuth permissions to post messages in Slack An n8n instance to host and execute the workflow Customization Replace Slack messaging with email, Discord, Microsoft Teams, Telegram, or another service. Modify the weather data format for different output preferences. Set up scheduled weather updates for specific locations. Use Cases Instantly check the weather for any location directly in Slack. Automate weather reports for team members or projects. Useful for remote teams, outdoor event planning, or general weather tracking. Setup Instructions Create a custom Slack app: Go to api.slack.com/apps and create a new app. Add a Slash Command (/weather) with the webhook URL from n8n. Enable OAuth scopes for sending messages. Deploy the webhook β Ensure it can receive and process Slack commands. Run the workflow β Type /weather [cityname] in Slack and receive instant weather updates.
by Mind-Front
Description: The closest definition to this workflow is a cheaper Modular Version of Perplexity online API empowered by LLM models that outperform the Perplexity Lama Model. This flow provides a seamless way to conduct detailed web searches, extract data, and generate insightful reports based on real-time information. It provides a webhook-based flow that gets any search question and reports back the results via a multi-level web search analysis and domain-specific emulation of an agent to deliver an unbiased expert report. This Flow is Ideal for market research, competitive analysis, or any scenario where actionable, structured insights are needed. A more complete, step-by-step guide is provided within the workflow, ensuring you have all the details to set up and customize each component. This tool is designed to function similarly to Perplexity by performing semantic search, reranking, and follow-up queries. However, it offers a unique advantageβcomplete customization at every stage. Modify any part of the process, from query refinement to data extraction, allowing you to tailor the workflow to your specific needs. Key Features: AI-Powered Query Generation and Expert Emulation**: Uses Google Gemini to transform user queries into expert-level searches, providing accurate and context-aware results. Dual-Stage Semantic Search with Intelligent Reranking**: Performs an initial search, reranks results, and refines the query based on findings to conduct a second, more targeted search. Top-Result Data Extraction**: Extracts content from the top three results of each search, capturing relevant insights from six total sources. Customizable API Options**: Pre-configured with free APIs (Google Gemini, DuckDuckGo, and Article Extraction APIs) but easily adaptable to other APIs if preferred. Automated, Insightful Reporting**: Synthesizes data into a cohesive report, providing expert-level insights tailored to the userβs query. Instructions for API Setup: This workflow is designed to work with free-tier APIs, offering a cost-effective way to retrieve high-quality data. Hereβs how to set up each API, with detailed instructions included in the workflow: Google Gemini API (for Query Generation and Analysis): Visit Google AI Studio and log in. Create a free API key under "Get API Key" β "Create API Key in New Project." The free tier includes up to 15 requests per minute, 1 million tokens per minute, and up to 1,500 requests per day. Brave Search API (for Web Search): To attain the free web search API tier from Brave, follow these steps: Visit api.search.brave.com Create an account Subscribe to the free plan (no charge) Navigate to the API Keys section Generate an API key. For the subscription type, choose "Free". Article Extraction API (for Content Extraction): Register on RapidAPI.com and subscribe to the Article Extraction API. The free plan allows up to 300 extractions per month. Enter your API key in each of the 6 extraction nodes for content retrieval. Alternative: In the workflow, we have provided the full instructions on how to replace the current flow with alternative API Keys and provided suggestions such as Scraper Tech API. Additional Tip: To use other APIs, you can generate a cURL request in RapidAPIβs playground, and then paste it into the HTTP Request node in n8n. This approach streamlines integration by automatically filling in headers and request details. Why Choose This Workflow? The Intelligent Online Web Researcher offers an all-in-one solution for complex, customizable online research. Unlike other tools that provide automated semantic search, this workflow is fully modifiable, allowing you to tailor each step, from the initial query and reranking to data extraction and reporting. With built-in instructions and a structure thatβs easy to adapt, itβs ideal for commercial applications that require real-time, high-quality insights. Tags: Online Research, Web Search, Market Analysis, Web Search Automation, Data Extraction, Semantic Search, API Integration, Competitive Intelligence, Business Intelligence, Real-Time Reporting, Web Scrape, Data Crawler, Perplexity