by David Olusola
📊 Google Sheets MCP Workflow – AI Meets Spreadsheets! 😄 ✨ What It Does This n8n workflow lets you chat with your spreadsheets using AI + MCP! From reading and updating data to creating sheets, it’s your smart assistant for Google Sheets 📈🤖 🚀 Cool Features 💬 Natural language commands (e.g. "Add a new lead: John Doe") ✏️ Full CRUD (Create, Read, Update, Delete) 🧠 AI-powered analysis & smart workflows 🗂️ Multi-sheet support 🔗 Works with ChatGPT, Claude, and more (via MCP) 💡 Use Cases Data Tasks: “Update status to 'Done' in row 3” Sheet Ops: “Create a ‘Marketing 2024’ sheet” Business Flows: “Summarize top sales from Q2” 🛠️ Quick Setup Import Workflow into n8n Copy the JSON In n8n → Import JSON → Paste & Save ✅ Connect Google Sheets Create a project in Google Cloud Enable Sheets & Drive APIs Create OAuth2 credentials In n8n → Add Google Sheets OAuth2 credential → Connect 🔐 Add Your Credentials Get your credential ID Open each Google Sheets node → Update with your new credential ID Link to AI (Optional 😊) MCP webhook is pre-set Plug it into your AI tool (like ChatGPT) Send test command → Watch the magic happen ✨ ✅ Test It Out Try these fun commands: 🆕 "Add entry: Jane Doe, janed@example.com" 🔍 "Read data from Sales 2024" 🧹 "Clear data from A1:C5" ➕ "Create sheet 'Budget 2025'" ❌ "Delete sheet 'Test'" 🧠 MCP Command List (AI-Callable Functions) These are the tasks the AI can perform via MCP: Add a new entry to a sheet Read data from a sheet Update a row in a sheet Delete a row from a sheet Create a new sheet Delete an existing sheet Clear data from a specific range Summarize data from a sheet using AI ⚙️ Tips & Fixes OAuth2 Errors? Re-authenticate and check scopes Confirm redirect URI is exact Permissions? Spreadsheet must be shared with edit access Use service accounts for production Webhook Not Firing? Double-check the URL Trigger it manually to test
by Dvir Sharon
💼 LinkedIn Job Finder Automation using Bright Data API & Google Sheets A comprehensive n8n automation that searches LinkedIn job postings using Bright Data’s API and automatically organizes results in Google Sheets for efficient job hunting and recruitment workflows. 📋 Overview This workflow provides an automated LinkedIn job search solution that collects job postings based on your search criteria and organizes them in Google Sheets. Perfect for job seekers, recruiters, HR professionals, and talent acquisition teams. ✨ Key Features 🔍 Smart Job Search:** Form-based input for city, job title, country, and job type 🛍 LinkedIn Integration:** Uses Bright Data’s LinkedIn dataset for accurate job posting data 📊 Automated Organization:** Populates Google Sheets with structured job data 📧 Real-time Processing:** Processes job search requests in real-time 📈 Data Storage:** Stores job details including company info, locations, and apply links 🔄 Batch Processing:** Handles multiple job postings efficiently ⚡ Fast & Reliable:** Built-in error handling for scraping 🎯 Customizable Filters:** Advanced job filtering based on criteria 🎯 What This Workflow Does Input Job Search Criteria:** City, job title, country, and optional job type Search Parameters:** Configurable filters and limits Output Preferences:** Google Sheets destination Processing Steps Form Submission Data Request to Bright Data API Status Monitoring Data Extraction Data Filtering Sheet Update Error Handling Output Data Points Field Description Example Job Title Position title from posting Senior Software Engineer Company Name Employer company name Tech Solutions Inc. Job Detail Job summary/description Remote position requiring 5+ years… Location Job location San Francisco, CA Company URL Company profile link View Profile Apply Link Direct application link Apply Now 🚀 Setup Instructions Prerequisites n8n instance (self-hosted or cloud) Google account with Sheets access Bright Data account with LinkedIn dataset access Steps Import the Workflow: Use JSON import in n8n Configure Bright Data: Add API credentials and dataset ID Configure Google Sheets: Create sheet, set credentials, map columns Update Workflow Settings: Replace placeholders with your actual data Test & Activate: Submit test form and verify data in Google Sheets 📖 Usage Guide Submitting Job Searches Go to your webhook URL and fill in the form with: City:** e.g., New York Job Title:** e.g., Software Engineer Country:** e.g., US Job Type:** Optional (Full-Time, Remote, etc.) Understanding Results Comprehensive job data Company info and profile links Direct application links Location and job descriptions Customizing Search Parameters Edit the Create Snapshot ID node to change: Time range (e.g., “Past month”) Result limits Company filters 🔧 Customization Options More Data Points:** Add salary, seniority, applicants, etc. Custom Form Fields:** Add filters for salary, experience, industry Multiple Sheets:** Route results by job type or location 🚨 Troubleshooting Bright Data connection failed:** Check API credentials and dataset access No job data extracted:** Verify search parameters and API limits Google Sheets permission denied:** Re-authenticate and check sharing Form not working:** Check webhook URL and field mappings Filter issues:** Review logic and data types Execution failed:** Check logs, retry logic, and network status 📊 Use Cases & Examples Job Seeker Dashboard:** Automate job search and track applications Recruitment Pipeline:** Source candidates and monitor hiring trends Market Research:** Analyze job trends and salary benchmarks HR Analytics:** Support workforce planning and competitive insights ⚙️ Advanced Configuration Batch Processing:** Queue multiple searches with delays Search History:** Track and analyze past searches Tool Integration:** Connect to CRM, Slack, databases, BI tools 📈 Performance & Limits Processing Time:** 30–60 seconds per search Concurrent Requests:** 2–3 (depends on Bright Data plan) Data Accuracy:** 95%+ Success Rate:** 90%+ Daily Capacity:** 50–200 searches Memory:** ~50MB per execution API Calls:** 3–4 Bright Data + 1 Google Sheets per search 🤝 Support & Community n8n Community:** community.n8n.io Documentation:** docs.n8n.io Bright Data Support:** Via your Bright Data dashboard GitHub Issues:** Report bugs and request features 🎯 Ready to Use! Your workflow is ready for automated LinkedIn job searching. Customize it to your recruiting or job search needs. Webhook URL: https://your-n8n-instance.com/webhook/linkedin-job-finder What Gets Extracted: * ✅ Job Title * ✅ Company Information * ✅ Location Data * ✅ Job Details * ✅ Application Links * ✅ Processing Timestamps ### Use Cases: * 🔍 Job Search Automation * 📊 Recruitment Intelligence * 📝 Market Research * 🎯 HR Analytics
by Ranjan Dailata
Who this is for The Async Structured Bulk Data Extract with Bright Data Web Scraper workflow is designed for data engineers, market researchers, competitive intelligence teams, and automation developers who need to programmatically collect and structure high-volume data from the web using Bright Data's dataset and snapshot capabilities. This workflow is built for: Data Engineers - Building large-scale ETL pipelines from web sources Market Researchers - Collecting bulk data for analysis across competitors or products Growth Hackers & Analysts - Mining structured datasets for insights Automation Developers - Needing reliable snapshot-triggered scrapers Product Managers - Overseeing data-backed decision-making using live web information What problem is this workflow solving? Web scraping at scale often requires asynchronous operations, including waiting for data preparation and snapshots to complete. Manual handling of this process can lead to timeouts, errors, or inconsistencies in results. This workflow automates the entire process of submitting a scraping request, waiting for the snapshot, retrieving the data, and notifying downstream systems all in a structured, repeatable fashion. It solves: Asynchronous snapshot completion handling Reliable retrieval of large datasets using Bright Data Automated delivery of scraped results via webhook Disk persistence for traceability or historical analysis What this workflow does Set Bright Data Dataset ID & Request URL: Takes in the Dataset ID and Bright Data API endpoint used to trigger the scrape job HTTP Request: Sends an authenticated request to the Bright Data API to start a scraping snapshot job Wait Until Snapshot is Ready: Implements a loop or wait mechanism that checks snapshot status (e.g., polling every 30 seconds) until completion i.e ready state Download Snapshot: Downloads the structured dataset snapshot once ready Persist Response to Disk: Saves the dataset to disk for archival, review, or local processing Webhook Notification: Sends the final result or a summary of it to an external webhook Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. Update the Set Dataset Id, Request URL for setting the brand content URL. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. How to customize this workflow to your needs Polling Strategy : Adjust polling interval (e.g., every 15–60 seconds) based on snapshot complexity Input Flexibility : Accept datasetId and request URL dynamically from a webhook trigger or input form Webhook Output : Send notifications to - Internal APIs – for use in dashboards Zapier/Make – for multi-step automation Persistence Save output to: Remote FTP or SFTP storage Amazon S3, Google Cloud Storage etc.
by Solido AI
How it works: This bot operates in a continuous WhatsApp monitoring loop. It analyzes messages to detect keywords in common questions (like hours, prices, and location) and sends automatic replies with predefined information. For unrecognized questions, it directs the user to manual assistance. Set up steps: The initial setup involves integrating with the WhatsApp API, registering keywords and their respective responses, and defining the fallback flow. It takes only a few minutes to have the bot running with essential information.
by Solido AI
How it works: This system functions by receiving expenses via webhook POST. It validates the data, stores it in Google Sheets, and, daily at 8 PM, generates and sends financial summaries. Automatic categorization simplifies the organization of expenses. Set up steps: Setup involves creating the Google Sheet, configuring the webhook, and defining the categorization rules. The process is quick and intuitive, taking about 10-15 minutes for the system to be ready to receive your expenses.
by David Ashby
Complete MCP server exposing 3 Search Services 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 Search Services 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 Search Services 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.archive.org • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (3 total) 🔧 Search (3 endpoints) • GET /search/v1/fields: Fields that can be requested • GET /search/v1/organic: Return relevance-based results from search queries • GET /search/v1/scrape: Scrape search results from Internet Archive, allowing a scrolling cursor 🤖 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 Search Services 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.
by Manuel
Effortlessly optimize your workflow by automatically save all files you are receiving on Telegram to a Google Drive Folder. How it works Retrieve a message sent to your Telegram Bot containing a file Upload the file to your Google Drive Folder Set up Steps Create a Telegram Account and a Telegram Bot and connect your Telegram Bot to n8n by following the official n8n instructions Create a Google Drive Folder Connect your Google Drive with n8n following the official n8n instructions Set the right folder in the Google Drive node Use case examples Backup and Recovery Cross-Platform Access File Organization and Management File Collaboration and Sharing Storage Space Management
by Kirill Khatkevich
This workflow is a comprehensive solution for digital marketers, performance agencies, and e-commerce brands looking to scale their creative testing process on Meta Ads efficiently. It eliminates the tedious manual work of uploading assets, creating campaigns, and setting up ads one by one. Use Case Manually launching weekly creative tests is time-consuming and prone to errors. This workflow solves that problem by creating a fully automated pipeline: from a creative asset in a folder to a complete, ready-to-launch (but paused) ad structure in your Meta Ads account. It's perfect for teams that want to: Save hours of manual work every week. Systematically test a high volume of creatives. Maintain a structured and consistent campaign naming convention. Keep a detailed log of all created assets for data-driven performance analysis. How it Works The workflow is structured into four logical blocks: 1. Configuration & Scheduling: The workflow runs on a weekly schedule. A central "Configuration" Set node at the beginning holds all key variables (Ad Account ID, Page ID, Pixel ID, making it incredibly easy to adapt the template for different projects. 2. Creative Ingestion & Processing: It scans a specific Google Drive folder for new image and video files. Using an IF node, it branches the logic based on the file type. Each file is uploaded to the Meta Ads library, and a corresponding Ad Creative is built with a pre-defined destination URL. 3. Campaign & Ad Set Assembly: The workflow creates a single new Campaign with an OUTCOME_SALES objective. It then creates a single Ad Set optimized for OFFSITE_CONVERSIONS (e.g., "Add to Cart"), using the Pixel ID from the configuration. A Merge node intelligently combines the single Ad Set ID with every creative processed in the previous block, preparing the data for the final step. 4. Ad Creation & Data Logging: The workflow iterates through the prepared data, creating a unique Ad for each creative. Upon the successful creation of each ad, a new row is appended to a Google Sheet, logging all relevant IDs (CampaignID, AdSetID, AdID, CreativeID) and metadata for a complete audit trail. Setup Instructions To use this template, you need to configure a few key nodes. 1. Credentials: Connect your Meta Ads account. Connect your Google account (for both Drive and Sheets). 2. The ⚙️ Configuration Node (Set node): This is the most important step. Open the first Set node and fill in your specific values: adAccountId: Your Meta Ad Account ID. pageId: The ID of the Facebook Page you're advertising for. pixelId: Your Meta Pixel ID for conversion tracking. 3. Google Sheets Node (Save Full Report to Sheet): Select your spreadsheet and the specific sheet where you want to save the reports. Make sure your sheet has columns with the following headers: CampaignID, AdSetID, AdID, CreativeID, FileName, MimeType, Timestamp. 4. Check URLs and IDs in HTTP Request Nodes: The template is configured to use the variables from the ⚙️ Configuration node. Double-check that the URLs in the Create Campaign, Create Ad Set, and Create ... Creative nodes correctly reference these variables (e.g., .../act_{{ $('⚙️ Configuration Meta Ads').item.json.adAccountId }}/campaigns). Verify the link in the Create Video Creative and Create Image Creative nodes points to your desired landing page. 5. Activate the Workflow: Set your desired schedule in the Schedule Trigger node. Save and activate the workflow. Further Ideas & Customization This workflow is a powerful foundation. You can easily extend it to: Create a second workflow** that runs a week later, reads the Google Sheet, and pulls performance data for all the ads created. A/B test ad copy** by adding different text variations from a spreadsheet. Add a Slack or Email notification** at the end to confirm that the weekly campaign launch was successful.
by Ricardo Espinozaas
Use Case When having a call with a new potential customer, one of the keys to getting the most out of the call is to find out as much information as you can about them before the call. Normally this involves a lot of manual research before every call. This workflow automates this tedious work for you. What this workflow does The workflow runs every time a new call is booked via your Calendly. It then filters out personal emails, before enriching the email. If the email is attached to a company it enriches the company and upserts it in your Hubspot CRM. Setup Add Clearbit, Hubspot, and Calendly credentials. Click on Test workflow. Book a meeting on Calendly so the event starts the workflow. Be aware that you can adapt this workflow to work with your enrichment tool, CRM, and booking tool of choice.
by David Ashby
Complete MCP server exposing 2 IP Geolocation 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 IP Geolocation API 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 IP Geolocation 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.bigdatacloud.net • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Data (2 endpoints) • GET /data/ip-geolocation-full: IP Geolocation with Confidence Area and Hazard Report API • GET /data/ip-geolocation-with-confidence: IP Geolocation with Confidence Area API 🤖 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 IP Geolocation 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.
by David Ashby
🛠️ Clearbit Tool MCP Server Complete MCP server exposing all Clearbit Tool operations to AI agents. Zero configuration needed - all 3 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Clearbit Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Clearbit Tool tool with full error handling 📋 Available Operations (3 total) Every possible Clearbit Tool operation is included: 🔧 Company (2 operations) • Autocomplete a company • Enrich a company 👥 Person (1 operations) • Enrich a person 🤖 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 Clearbit 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 Clearbit 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.
by David Ashby
Complete MCP server exposing 2 Catalog 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 Catalog API 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 Catalog 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.ebay.com{basePath} • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Product (1 endpoints) • GET /product/{epid}: Get {Epid} 🔧 Product_Summary (1 endpoints) • GET /product_summary/search: Search Product Summaries 🤖 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 Catalog 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.