Workflow Templates

LinkedIn & Indeed Job Scraper with Bright Data & Google Sheets Export Overview This n8n workflow automates the process of scraping job listings from both LinkedIn and Indeed platforms simultaneously, combining results, and exporting data to Google Sheets for comprehensive job market analysis. It integrates with Bright Data for professional web scraping, Google Sheets for data storage, and provides intelligent status monitoring with retry mechanisms. Workflow Components 1. 📝 Trigger Input Form Type**: Form Trigger Purpose**: Initiates the workflow with user-defined job search criteria Input Fields**: City (required) Job Title (required) Country (required) Job Type (optional dropdown: Full-Time, Part-Time, Remote, WFH, Contract, Internship, Freelance) Function**: Captures user requirements to start the dual-platform job scraping process 2. 🧠 Format Input for APIs Type**: Code Node (JavaScript) Purpose**: Prepares and formats user input for both LinkedIn and Indeed APIs Processing**: Standardizes location and job title formats Creates API-specific input structures Generates custom output field configurations Function**: Ensures compatibility with both Bright Data datasets 3. 🚀 Start Indeed Scraping Type**: HTTP Request (POST) Purpose**: Initiates Indeed job scraping via Bright Data Endpoint**: https://api.brightdata.com/datasets/v3/trigger Parameters**: Dataset ID: gd_lpfll7v5hcqtkxl6l Include errors: true Type: discover_new Discover by: keyword Limit per input: 2 Custom Output Fields**: jobid, company_name, job_title, description_text location, salary_formatted, company_rating apply_link, url, date_posted, benefits 4. 🚀 Start LinkedIn Scraping Type**: HTTP Request (POST) Purpose**: Initiates LinkedIn job scraping via Bright Data (parallel execution) Endpoint**: https://api.brightdata.com/datasets/v3/trigger Parameters**: Dataset ID: gd_l4dx9j9sscpvs7no2 Include errors: true Type: discover_new Discover by: keyword Limit per input: 2 Custom Output Fields**: job_posting_id, job_title, company_name, job_location job_summary, job_employment_type, job_base_pay_range apply_link, url, job_posted_date, company_logo 5. 🔄 Check Indeed Status Type**: HTTP Request (GET) Purpose**: Monitors Indeed scraping job progress Endpoint**: https://api.brightdata.com/datasets/v3/progress/{snapshot_id} Function**: Checks if Indeed dataset scraping is complete 6. 🔄 Check LinkedIn Status Type**: HTTP Request (GET) Purpose**: Monitors LinkedIn scraping job progress Endpoint**: https://api.brightdata.com/datasets/v3/progress/{snapshot_id} Function**: Checks if LinkedIn dataset scraping is complete 7. ⏱️ Wait Nodes (60 seconds each) Type**: Wait Node Purpose**: Implements intelligent polling mechanism Duration**: 1 minute Function**: Pauses workflow before rechecking scraping status to prevent API overload 8. ✅ Verify Indeed Completion Type**: IF Condition Purpose**: Evaluates Indeed scraping completion status Condition**: status === "ready" Logic**: True: Proceeds to data validation False: Loops back to status check with wait 9. ✅ Verify LinkedIn Completion Type**: IF Condition Purpose**: Evaluates LinkedIn scraping completion status Condition**: status === "ready" Logic**: True: Proceeds to data validation False: Loops back to status check with wait 10. 📊 Validate Indeed Data Type**: IF Condition Purpose**: Ensures Indeed returned job records Condition**: records !== 0 Logic**: True: Proceeds to fetch Indeed data False: Skips Indeed data retrieval 11. 📊 Validate LinkedIn Data Type**: IF Condition Purpose**: Ensures LinkedIn returned job records Condition**: records !== 0 Logic**: True: Proceeds to fetch LinkedIn data False: Skips LinkedIn data retrieval 12. 📥 Fetch Indeed Data Type**: HTTP Request (GET) Purpose**: Retrieves final Indeed job listings Endpoint**: https://api.brightdata.com/datasets/v3/snapshot/{snapshot_id} Format**: JSON Function**: Downloads completed Indeed job data 13. 📥 Fetch LinkedIn Data Type**: HTTP Request (GET) Purpose**: Retrieves final LinkedIn job listings Endpoint**: https://api.brightdata.com/datasets/v3/snapshot/{snapshot_id} Format**: JSON Function**: Downloads completed LinkedIn job data 14. 🔗 Merge Results Type**: Merge Node Purpose**: Combines Indeed and LinkedIn job results Mode**: Merge all inputs Function**: Creates unified dataset from both platforms 15. 📊 Save to Google Sheet Type**: Google Sheets Node Purpose**: Exports combined job data for analysis Operation**: Append rows Target**: "Compare" sheet in specified Google Sheet document Data Mapping**: Job Title, Company Name, Location Job Detail (description), Apply Link Salary, Job Type, Discovery Input Workflow Flow Input Form → Format APIs → [Indeed Trigger] + [LinkedIn Trigger] ↓ ↓ Check Status Check Status ↓ ↓ Wait 60s Wait 60s ↓ ↓ Verify Ready Verify Ready ↓ ↓ Validate Data Validate Data ↓ ↓ Fetch Indeed Fetch LinkedIn ↓ ↓ └─── Merge Results ───┘ ↓ Save to Google Sheet Configuration Requirements API Keys & Credentials Bright Data API Key**: Required for both LinkedIn and Indeed scraping Google Sheets OAuth2**: For data storage and export access n8n Form Webhook**: For user input collection Setup Parameters Google Sheet ID**: Target spreadsheet identifier Sheet Name**: "Compare" tab for job data export Form Webhook ID**: User input form identifier Dataset IDs**: Indeed: gd_lpfll7v5hcqtkxl6l LinkedIn: gd_l4dx9j9sscpvs7no2 Key Features Dual Platform Scraping Simultaneous LinkedIn and Indeed job searches Parallel processing for faster results Comprehensive job market coverage Platform-specific field extraction Intelligent Status Monitoring Real-time scraping progress tracking Automatic retry mechanisms with 60-second intervals Data validation before processing Error handling and timeout management Smart Data Processing Unified data format from both platforms Intelligent field mapping and standardization Duplicate detection and removal Rich metadata extraction Google Sheets Integration Automatic data export and storage Organized comparison format Historical job search tracking Easy sharing and collaboration Form-Based Interface User-friendly job search form Flexible job type filtering Multi-country support Real-time workflow triggering Use Cases Personal Job Search Comprehensive multi-platform job hunting Automated daily job searches Organized opportunity comparison Application tracking and management Recruitment Services Client job search automation Market availability assessment Competitive salary analysis Bulk candidate sourcing Market Research Job market trend analysis Salary benchmarking studies Skills demand assessment Geographic opportunity mapping HR Analytics Competitor hiring intelligence Role requirement analysis Compensation benchmarking Talent market insights Technical Notes Polling Interval**: 60-second status checks for both platforms Result Limiting**: Maximum 2 jobs per input per platform Data Format**: JSON with structured field mapping Error Handling**: Comprehensive error tracking in all API requests Retry Logic**: Automatic status rechecking until completion Country Support**: Adaptable domain selection (indeed.com, fr.indeed.com) Form Validation**: Required fields with optional job type filtering Merge Strategy**: Combines all results from both platforms Export Format**: Standardized Google Sheets columns for easy analysis Sample Data Output | Field | Description | Example | |-------|-------------|---------| | Job Title | Position title | "Senior Software Engineer" | | Company Name | Hiring organization | "Tech Solutions Inc." | | Location | Job location | "San Francisco, CA" | | Job Detail | Full description | "We are seeking a senior developer..." | | Apply Link | Direct application URL | "https://company.com/careers/123" | | Salary | Compensation info | "$120,000 - $150,000" | | Job Type | Employment details | "Full-time, Remote" | Setup Instructions Import Workflow: Copy JSON configuration into n8n Configure Bright Data: Add API credentials for both datasets Setup Google Sheets: Create target spreadsheet and configure OAuth Update References: Replace placeholder IDs with your actual values Test Workflow: Submit test form and verify data export Activate: Enable workflow and share form URL with users For any questions or support, please contact: info@incrementors.com or fill out this form: https://www.incrementors.com/contact-us/

Complete MCP server exposing 1 IP2Proxy Proxy Detection 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 IP2Proxy Proxy Detection 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 IP2Proxy Proxy Detection 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 https://api.ip2proxy.com • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 total) 🔧 General (1 endpoints) • GET /: Check Proxy IP 🤖 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 IP2Proxy Proxy Detection 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.

Complete MCP server exposing all Mailcheck Tool operations to AI agents. Zero configuration needed - 1 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Mailcheck Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Mailcheck Tool tool with full error handling 📋 Available Operations (1 total) Every possible Mailcheck Tool operation is included: 🔧 Email (1 operations) • Check an email 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Mailcheck Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Mailcheck Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

! n8n Workflow: HTML to PDF Generator This n8n workflow converts HTML content into a styled PDF and returns it as a response via a webhook. The workflow receives HTML input, processes it using CustomJS's PDF toolkit, and sends back the resulting PDF to the original webhook requester. @custom-js/n8n-nodes-pdf-toolkit Features: Webhook Trigger**: Accepts incoming requests with HTML content. HTML to PDF Conversion**: Uses CustomJS to transform HTML into a PDF. Response**: Sends the generated PDF back to the webhook response. Requirements: Self-hosted** n8n instance A CustomJS API key for HTML to PDF conversion HTML content** to be converted into a PDF Workflow Steps: Webhook Trigger: Accepts incoming HTTP requests with HTML content. This data is passed to the next node for processing. HTML to PDF Conversion: Uses the CustomJS node to convert the incoming HTML into a PDF document. You can customize the HTML content to match the design requirements. Respond to Webhook: Sends the generated PDF as a binary response to the original webhook request. Setup Guide: 1. Configure CustomJS API Sign up at CustomJS. Retrieve your API key from the profile page. Add your API key as n8n credentials. 2. Design Workflow Create a Webhook: Set up a webhook to trigger the workflow when HTML content is received. Prepare HTML Content: The incoming request should include the HTML content you wish to convert into a PDF. Configure HTML to PDF Node: Use the HTML to PDF node to convert the provided HTML into a PDF. The node uses the HTML input to generate a PDF using the CustomJS API. Respond with the PDF: The Respond to Webhook node will send the generated PDF back to the original requester as a binary response. Example HTML Input: Hello CustomJS! CustomJS provides the missing toolset for your no-code projects Result PDF

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

Description This workflow automates document processing using LlamaParse to extract and analyze text from various file formats. It intelligently processes documents, extracts structured data, and delivers actionable insights through multiple channels. How It Works Document Ingestion & Processing 📄 Monitors Gmail for incoming attachments or accepts documents via webhook Validates file formats against supported LlamaParse extensions Uploads documents to LlamaParse for advanced text extraction Stores original documents in Google Drive for reference Intelligent Document Analysis 🧠 Automatically classifies document types (invoices, reports, etc.) Extracts structured data using customized AI prompts Generates comprehensive document summaries with key insights Converts unstructured text into organized JSON data Invoice Processing Automation 💼 Extracts critical invoice details (dates, amounts, line items) Organizes financial data into structured formats Calculates tax breakdowns, subtotals, and payment information Maintains detailed records for accounting purposes Multi-Channel Delivery 📱 Saves extracted data to Google Sheets for tracking and analysis Sends concise summaries via Telegram for immediate review Creates searchable document archives in Google Drive Updates spreadsheets with structured financial information Setup Steps Configure API Credentials 🔑 Set up LlamaParse API connection Configure Gmail OAuth for email monitoring Set up Google Drive and Sheets integrations Add Telegram bot credentials for notifications Customize AI Processing ⚙️ Adjust document classification parameters Modify extraction templates for specific document types Fine-tune summary generation prompts Customize invoice data extraction schema Test and Deploy 🚀 Test with sample documents of various formats Verify data extraction accuracy Confirm notification delivery Monitor processing pipeline performance

An intelligent IT support agent that uses Azure AI Search for knowledge retrieval, Microsoft Entra ID integration for user management, and Jira for ticket creation. The agent can answer questions using internal documentation and perform administrative tasks like password resets. How It Works The workflow operates in three main sections: Agent Chat Interface: A chat trigger receives user messages and routes them to an AI agent powered by Google Gemini. The agent maintains conversation context using buffer memory and has access to multiple tools for different tasks. Knowledge Management: Users can upload documentation files (.txt, .md) through a form trigger. These documents are processed, converted to embeddings using OpenAI's API, and stored in an Azure AI Search index with vector search capabilities. Administrative Tools: The agent can query Microsoft Entra ID to find users, reset passwords, and create Jira tickets when issues need escalation. It uses semantic search to find relevant internal documentation before responding to user queries. The workflow includes a separate setup section that creates the Azure AI Search service and index with proper vector search configuration, semantic search capabilities, and the required field schema. Prerequisites To use this template, you'll need: n8n cloud or self-hosted instance Azure subscription with permissions to create AI Search services Microsoft Entra ID (Azure AD) access with user management permissions OpenAI API account for embeddings Google Gemini API access Jira Software Cloud instance Basic understanding of Azure resource management Setup Instructions Import the template into n8n. Configure credentials: Add Google Gemini API credentials Add OpenAI API credentials for embeddings Add Microsoft Azure OAuth2 credentials with appropriate permissions Add Microsoft Entra ID OAuth2 credentials Add Jira Software Cloud API credentials Update workflow parameters: Open the "Set Common Fields" nodes Replace <azure subscription id> with your Azure subscription ID Replace <azure resource group> with your target resource group name Replace <azure region> with your preferred Azure region Replace <azure ai search service name> with your desired service name Replace <azure ai search index name> with your desired index name Update the Jira project ID in the "Create Jira Ticket" node Set up Azure infrastructure: Run the manual trigger "When clicking 'Test workflow'" to create the Azure AI Search service and index This creates the vector search index with semantic search configuration Configure the vector store webhook: Update the "Invoke Query Vector Store Webhook" node URL with your actual webhook endpoint The webhook URL should point to the "Semantic Search" webhook in the same workflow Upload knowledge base: Use the "On Knowledge Upload" form to upload your internal documentation Supported formats: .txt and .md files Documents will be automatically embedded and indexed Test the setup: Use the chat interface to verify the agent responds appropriately Test knowledge retrieval with questions about uploaded documentation Verify Entra ID integration and Jira ticket creation Security Considerations Use least-privilege access for all API credentials Microsoft Entra ID credentials should have limited user management permissions Azure credentials need Search Service Contributor and Search Index Data Contributor roles OpenAI API key should have usage limits configured Jira credentials should be restricted to specific projects Consider implementing rate limiting on the chat interface Review password reset policies and ensure force password change is enabled Validate all user inputs before processing administrative requests Extending the Template You could enhance this template by: Adding support for additional file formats (PDF, DOCX) in the knowledge upload Implementing role-based access control for different administrative functions Adding integration with other ITSM tools beyond Jira Creating automated escalation rules based on query complexity Adding analytics and reporting for support interactions Implementing multi-language support for international organizations Adding approval workflows for sensitive administrative actions Integrating with Microsoft Teams or Slack for notifications

Nova AI Content Marketing Agent - LinkedIn & Facebook Automation This n8n template demonstrates how to create a complete AI-powered social media content creation and scheduling system that generates platform-optimized posts for LinkedIn and Facebook with custom images and human approval workflows. Possible use cases: Generate a full week of social media content from a single brand brief Create platform-specific content that maintains brand voice consistency Automate image generation with AI while maintaining quality control Schedule approved content across multiple social platforms Track and organize all content in centralized spreadsheets How it works The automation starts with a form submission collecting 10 brand variables (name, industry, demographics, etc.) Nova AI Agent analyzes the brand information and generates 6 distinct social media posts (3 LinkedIn professional, 3 Facebook community-focused) Content is split by platform and routed to separate image generation workflows Google Imagen 4 Ultra creates custom visuals for each post with platform-specific aspect ratios Each generated image is sent to Slack for human approval via interactive forms If feedback is provided, NanoBanana AI edits the image based on natural language instructions Approved images are uploaded to Google Drive with organized naming conventions All content data is logged to Google Sheets with image URLs and scheduling information Final posts are scheduled via Late API to respective social platforms The workflow loops through each post individually for quality control Requirements OpenRouter API credentials for GPT-5 Mini access Replicate API key for Google Imagen 4 Ultra and NanoBanana Slack OAuth2 credentials with bot permissions Google Drive OAuth2 credentials Google Sheets API access GetLate API key connected to LinkedIn and Facebook accounts Perplexity API for research enhancement (optional) HOW TO USE STEP 1 - Setup Form and Brand Variables Configure the Form Trigger webhook URL for brand data collection Update the 10 form fields with your specific industry placeholders Test the form submission to ensure data flows correctly STEP 2 - Configure AI Services Add your OpenRouter API credentials to both Chat Model nodes Add your Replicate API key to the HTTP Header Auth credential Configure Perplexity API credentials for research functionality Set up custom session keys for memory management STEP 3 - Setup Approval Workflow Add Slack OAuth2 credentials to both "Send message and wait" nodes Update the Slack channel ID to your preferred approval channel Configure the custom form fields for approval/feedback collection STEP 4 - Configure Storage and Scheduling Add Google Drive OAuth2 credentials and update the target folder ID Add Google Sheets credentials and update the spreadsheet ID Get your Late API key from getlate.dev and add to HTTP Header Auth Update the Late accountId in both Schedule Post nodes with your platform IDs STEP 5 - Customize Content Strategy Modify the Nova system prompt to match your brand voice requirements Adjust the visual style requirements in the AI Agent configuration Update posting date logic and timezone settings as needed Test the complete workflow with sample brand data

This workflow template, "Personal Assistant to Note Messages and Extract Namecard Information" is designed to streamline the processing of incoming messages on the LINE messaging platform. It integrates with powerful tools like Microsoft Teams , Microsoft To Do , OneDrive , and OpenRouter.ai to handle tasks such as saving notes, extracting namecard information, and organizing images. Whether you’re managing personal productivity or automating workflows for teams, this template offers a versatile and customizable solution. By leveraging this workflow, you can automate repetitive tasks, improve collaboration, and enhance efficiency in handling LINE messages. Who Is This Template For? This template is ideal for: Professionals: Who want to save important messages, extract data from namecards, or organize images automatically. Teams: Looking to integrate LINE messages into tools like Microsoft Teams and Microsoft To Do for better collaboration. Developers: Seeking to build intelligent workflows that process text, images, and other inputs from LINE. Business Owners: Who need to manage customer interactions, follow-ups, and task tracking efficiently. What Problem Does This Workflow Solve? Managing incoming messages on LINE can be time-consuming, especially when dealing with diverse input types like text, images, and namecards. This workflow solves that problem by: Automatically identifying and routing different message types (text, images, namecards) to appropriate actions. Extracting structured data from namecards and saving it for follow-up tasks. Uploading images to OneDrive and saving text messages to Microsoft Teams or Microsoft To Do for easy access. Sending real-time feedback to users via LINE to confirm that their messages have been processed. What This Workflow Does Receive Messages via LINE Webhook: The workflow is triggered whenever a user sends a message (text, image, or other types) to the LINE bot. Display Loading Animation: A loading animation is displayed to reassure the user that their request is being processed. Route Input Types: The workflow uses a Switch node to determine the type of input: Text Starting with "T": Adds the message as a task in Microsoft To Do. Plain Text: Saves the message in Microsoft Teams under a designated channel (e.g., "Notes"). Images: Identifies whether the image is a namecard, handwritten note, or other content, then processes accordingly. Unsupported formats trigger a polite response indicating the limitation. Process Namecards: *Images * If the image is identified as a namecard, the workflow extracts structured data (e.g., name, email, phone number) using OpenRouter.ai and saves it to Microsoft To Do for follow-up tasks. Save Images to OneDrive: Images are uploaded to OneDrive, renamed based on their unique message ID, and linked in Microsoft Teams for reference. Send Feedback via LINE: The workflow replies to the user with confirmation messages, such as "[ Task Created ]" or "[ Message Saved ]." Setup Guide Pre-Requisites Access to the LINE Developers Console to configure your webhook and bot. Accounts for Microsoft Teams , Microsoft To Do, and OneDrive with API access. An OpenRouter.ai account with credentials to access models like GPT-4o. Basic knowledge of APIs, webhooks, and JSON formatting. Step-by-Step Setup 1) Configure the LINE Webhook: Go to the LINE Developers Console and set up a webhook to receive incoming messages. Copy the Webhook URL from the Line Webhook node and paste it into the LINE Console. Remove any "test" configurations when moving to production. 2) Set Up Microsoft Integrations: Connect your Microsoft Teams, Microsoft To Do, and OneDrive accounts to the respective nodes in the workflow. 3) Set Up OpenRouter.ai: Create an account on OpenRouter.ai and obtain your API credentials. Connect your credentials to the OpenRouter nodes in the workflow. Test the Workflow: Simulate sending text, images, and namecards to the LINE bot to verify that all actions are processed correctly. How to Customize This Workflow to Your Needs Add More Actions: Extend the workflow to handle additional input types or integrate with other tools. Enhance Image Processing: Use advanced OCR tools to improve text extraction from complex images. Customize Feedback Messages: Modify the reply format to include emojis, links, or other formatting options. Expand Use Cases: Adapt the workflow for specific industries, such as sales or customer support, by tailoring the actions to relevant tasks. Why Use This Template? Versatile Automation: Handles multiple input types (text, images, namecards) with ease. Seamless Integration: Connects LINE messages to popular productivity tools like Microsoft Teams and To Do. Structured Data Extraction: Extracts and organizes data from namecards, saving time and effort. Real-Time Feedback: Keeps users informed about the status of their requests with instant notifications.

Who is this template for? This template is ideal for small businesses, agencies, and solo professionals who want to automate appointment scheduling and caller follow-up through a voice-based AI receptionist. If you’re using tools like Google Calendar, Airtable, and Vapi (Twilio), this setup is for you. What problem does this workflow solve? Manual call handling, appointment booking, and email coordination can be time-consuming and prone to errors. This workflow solves that by automating the receptionist role: answering calls, checking calendar availability, managing appointments, and storing call summaries—all without human intervention. What this workflow does This Agent Receptionist manages inbound voice calls and scheduling tasks using Vapi and Google Calendar. It checks availability, books or updates calendar events, sends email confirmations, and logs call details into Airtable. The workflow includes built-in logic for slot management, email triggers, and storing call transcripts. Setup Instructions Duplicate Airtable Base: Use this Airtable base templateBASE LINK Import Workflow: Load provided JSON into your n8n instance. Credentials: Connect your Google Calendar and Airtable credentials in n8n. Activate Workflow: Enable workflow to get live webhook URLs. Vapi Configuration: Paste provided system prompt into Vapi Assistant. Link the appropriate webhook URLs from n8n (GetSlots, BookSlots, UpdateSlots, CancelSlots, and end-of-call report). Disclaimer Optimized for cloud-hosted n8n instances. Self-hosted users should verify webhook and credential setups.

Who is this for? Public-facing professionals (developer advocates, founders, marketers, content creators) who get bombarded with LinkedIn messages that aren't actually for them - support requests when you're in marketing, sales inquiries when you're a devrel, partnership pitches when you handle content, etc. What problem is this workflow solving? When you're visible online, people assume you handle everything at your company. You end up spending hours daily playing human router, forwarding messages like "How do I reset my password?" or "What's your enterprise pricing?" to the right teams. This LinkedIn automation workflow stops you from being your company's unofficial customer service representative. What this workflow does This AI-powered LinkedIn DM management workflow automatically assesses incoming LinkedIn messages and routes them intelligently: Automated Message Assessment: Receives inbound LinkedIn messages via UniPile and looks up sender details from both personal and company LinkedIn profiles. Smart Route Matching: Compares the message content against your message routing workflow table in Notion, which contains: Question: "How can I become an n8n ambassador?" Description: "Route here when a user is requesting to become an n8n ambassador. Also when they're asking how they could do more to evangelize n8n in their city, or to start organizing n8n meetups and events in their city." Action: "Tell the user to open the following notion page which has details on ambassador program including how to apply, as well as perks of the program: https://www.notion.so/n8n-Ambassador-Program-d883b2a130e5448faedbebe5139187ea?pvs=21" AI Response Generation: When a message matches an existing route, this AI assistant generates a personalized response draft based on the "Action" instructions from your routing table. Human-in-the-Loop Approval: Sends the draft response to Slack with approve/reject buttons, so you maintain control while saving time. Draft can be edited from within Slack on desktop and mobile. Automated LinkedIn Responses: Once approved, sends the reply back via LinkedIn and marks the original message as handled. The result: You stop being a human switchboard and can focus on your actual job while people still get helpful, timely responses through automated customer service. You can also add routes for things you do handle but get asked about daily (like 'How do I join your beta?' or 'What's your content strategy?') to standardize your responses. Setup Sign up for a UniPile account and create a webhook under the Messaging section Set the callback URL to this workflow's production URL Generate a UniPile API key with all required scopes and store it in your n8n credentials Create a Slack app and enable interactive message buttons and webhooks Here is a slack App manifest template for easy deployment in slack: { "display_information": { "name": "Request Router", "description": "A bot that alerts when a new linkedin question comes in.", "background_color": "#12575e" }, "features": { "bot_user": { "display_name": "Request Router", "always_online": false } }, "oauth_config": { "scopes": { "bot": [ "chat:write", "chat:write.customize", "chat:write.public", "links:write", "im:history", "im:read", "im:write" ] } }, "settings": { "interactivity": { "is_enabled": true, "request_url": "Your webhook url here" }, "org_deploy_enabled": false, "socket_mode_enabled": false, "token_rotation_enabled": false } } Set up your Notion database with the three-column structure (Question, Description, Action) Configure the AI node with your preferred provider (OpenAI, Gemini, Ollama etc) Replace placeholder LinkedIn user and organization IDs with your own How to customize this workflow to your needs Database Options**: Swap Notion with Google Sheets, Airtable, or another database Filtering Logic**: Add custom filters based on keywords, message length, follower count, or business logic AI Customization**: Adjust the system prompt to match your brand tone and response goals Approval Platform**: Replace Slack with email, Discord, or another review platform Team Routing**: Use Slack metadata to route approvals to specific team members based on message category Enrichment**: Add secondary data enrichment using tools like Clearbit or FullContact Response Rules**: Create conditional logic for different response types based on sender profile or message content Perfect for anyone who's tired of being their company's accidental customer service department while trying to do their real job. This LinkedIn automation template was inspired by a live build done by Max Tkacz and Angel Menendez for The Studio.

Complete MCP server exposing 4 BikeWise API v2 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 BikeWise API v2 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 BikeWise API v2 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 https://bikewise.org/api • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (4 total) 🔧 V2 (4 endpoints) • GET /v2/incidents: Paginated incidents matching parameters • GET /v2/incidents/{id}: GET /v2/incidents/{id} • GET /v2/locations: Unpaginated geojson response • GET /v2/locations/markers: Unpaginated geojson response with simplestyled markers 🤖 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 BikeWise API v2 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.