Workflow Templates

Automated solution to extract and organize contact information from Upwork job postings, enabling direct outreach to potential clients who post jobs matching your expertise. 🚀 What It Does Scrapes job postings for contact information Extracts email addresses and social profiles Organizes leads in a structured format Enables direct outreach campaigns Tracks response rates 🎯 Perfect For Freelancers looking to expand their client base Agencies targeting specific industries Sales professionals in the gig economy Recruiters sourcing clients Digital marketing agencies ⚙️ Key Benefits ✅ Access to hidden contact information ✅ Expand your client base ✅ Beat the competition to opportunities ✅ Targeted outreach campaigns ✅ Higher response rates 🔧 What You Need Upwork account n8n instance Email service (for outreach) CRM (optional) 📊 Features Email pattern detection Social media profile extraction Company website discovery Lead scoring system Outreach tracking 🛠️ Setup & Support Quick Setup Start collecting leads in 20 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Take control of your freelance career with direct access to potential clients. Transform how you find and secure projects on Upwork.

This n8n workflow demonstrates a simple multi-agent setup to perform the task of competitor research. It showcases how using the HTTP request tool could reduce the number of nodes needed to achieve a workflow like this. How it works For this template, a source company is defined by the user which is sent to Exa.ai to find competitors. Each competitor is then funnelled through 3 AI agents that will go out onto the internet and retrieve specific datapoints about the competitor; company overview, product offering and customer reviews. Once the agents are finished, the results are compiled into a report which is then inserted in a notion database. Check out an example output here: https://jimleuk.notion.site/2d1c3c726e8e42f3aecec6338fd24333?v=de020fa196f34cdeb676daaeae44e110&pvs=4 Requirements An OpenAI account for the LLM. Exa.ai account for access to their AI search engine. SerpAPI account for Google search. Firecrawl.dev account for webscraping. Notion.com account for database to save final reports. Customising the workflow Add additional agents to gather more datapoints such as SEO keywords and metrics. Not using notion? Feel free to swap this out for your own database.

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights This template demonstrates the Customer Insights scenario where Trustpilot reviews can be quickly grouped by similarity and an AI agent can generate insights on those groupings. With this workflow, marketers can save days and even weeks of work breaking down their own or competitor reviews and identify frequently mentioned positives and negatives. Sample Output: https://docs.google.com/spreadsheets/d/e/2PACX-1vQ6ipJnXWXgr5wlUJnhioNpeYrxaIpsRYZCwN3C-fFXumkbh9TAsA_JzE0kbv7DcGAVIP7az0L46_2P/pubhtml How it works Trustpilot reviews are scraped for a particular company using the HTTP request node. Reviews are then inserted into a Qdrant collection carefully tagged with the question and Trustpilot metadata. Reviews are fetched and put through a clustering algorithm using the Python Code node. The Qdrant points are returned in clustered groups. Each group is looped to fetch the payloads of the points and feed them to the AI agent to summarise and generate insights for. The resulting insights and raw responses are then saved to the Google Spreadsheet for further analysis by the marketer. Requirements Qdrant Vectorstore for storing embeddings. OpenAI account for embeddings and LLM. Customising the Template Adjust clustering parameters which make sense for your data. Consider expanding date range of reviews for insights over common intervals: 3mth, 6mth and YTD.

Complete MCP server exposing all LoneScale Tool operations to AI agents. Zero configuration needed - all 2 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 LoneScale Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n LoneScale Tool tool with full error handling 📋 Available Operations (2 total) Every possible LoneScale Tool operation is included: 📝 List (1 operations) • Create a list 🔧 Item (1 operations) • Create a item 🤖 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 LoneScale 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 LoneScale 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.

Complete MCP server exposing all Hacker News 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 Hacker News Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Hacker News Tool tool with full error handling 📋 Available Operations (3 total) Every possible Hacker News Tool operation is included: 🔧 All (1 operations) • Get many items 🔧 Article (1 operations) • Get an article 👤 User (1 operations) • Get a user 🤖 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 Hacker News 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 Hacker News 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.

How it works This workflow demonstrates how to use n8n to serve a complete, styled HTML webpage. It acts as a mini web server, responding to browser requests with your custom HTML content. Webhook Trigger: The workflow starts with a Webhook node configured to listen for GET requests on a specific path. When you visit this node's Production URL in a browser, it triggers the workflow. Respond with HTML: The Respond to Webhook node is configured to send a response back to the browser. Content-Type Header: It sets a crucial response header, Content-Type: text/html, which tells the browser to render the response as a webpage, not just plain text. HTML Body: The entire HTML, CSS, and JavaScript for the webpage is pasted directly into the Body field of this node. When activated, visiting the webhook URL will instantly display the custom webpage. Set up steps Setup time: < 1 minute This workflow is ready to use out-of-the-box. Activate the workflow. Open the Your WebPage (Webhook) node and copy its Production URL. Paste the URL into your browser to see the live tutorial page. To use your own HTML, simply open the Site (Respond to Webhook) node and replace the content in the Body field with your own code.

Complete MCP server exposing 2 NPR Station Finder Service 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 NPR Station Finder Service 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 NPR Station Finder Service 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://station.api.npr.org • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 V3 (2 endpoints) • GET /v3/stations: Get Station 1 • GET /v3/stations/{stationId}: Retrieve metadata for the station with the given numeric ID 🤖 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 NPR Station Finder Service 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 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.

Complete MCP server exposing 2 Mobility 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 Mobility 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 Mobility 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://developer.o2.cz/mobility/sandbox/api • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Info (1 endpoints) • GET /info: Retrieve Application Info 🔧 Transit (1 endpoints) • GET /transit/{from}/{to}: Transit between basic residential units 🤖 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 Mobility 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 2 Negotiation 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 Negotiation 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 Negotiation 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) 🔧 Find_Eligible_Items (1 endpoints) • GET /find_eligible_items: Find Eligible Listings 🔧 Send_Offer_To_Interested_Buyers (1 endpoints) • POST /send_offer_to_interested_buyers: Send Discount Offer 🤖 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 Negotiation 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.

Video Guide I prepared a comprehensive guide detailing how to automate the parsing of invoices using n8n and LlamaParse, seamlessly capturing and storing vital billing information. Youtube Link Who is this for? This workflow is ideal for finance teams, accountants, and business operations managers who need to streamline invoice processing. It is particularly helpful for organizations seeking to reduce manual entry errors and improve efficiency in managing billing information. What problem does this workflow solve? Manually processing invoices can be time-consuming and error-prone. This automation eliminates the need for manual data entry by capturing invoice details directly from uploaded documents and storing structured data efficiently. This enhances productivity and accuracy across financial operations. What this workflow does The workflow leverages n8n and LlamaParse to automatically detect new invoices in a designated Google Drive folder, parse essential billing details, and store the extracted data in a structured format. The key functionalities include: Real-time detection of new invoices via Google Drive triggers. Automated HTTP requests to initiate parsing through Lama Cloud. Structured storage of invoice details and line items in a database for future reference. Google Drive Integration: Monitors a specific folder in Google Drive for new invoice uploads. Parsing with LlamaParse: Automatically sends invoices for parsing and processes results through webhooks. Data Storage in Airtable: Creates records for invoices and their associated line items, allowing for detailed tracking. Setup N8N Workflow Google Drive Trigger: Set up a trigger to detect new files in a specified folder dedicated to invoices. File Upload to LlamaParse: Create an HTTP request that sends the invoice file to LlamaParse for parsing, including relevant header settings and webhook URL. Webhook Processing: Establish a webhook node to handle parsed results from LlamaParse, extracting needed invoice details effectively. Invoice Record Creation: Create initial records for invoices in your database using the parsed details received from the webhook. Line Item Processing: Transform string data into structured line item arrays and create individual records for each item linked to the main invoice.

How it works This template is an interactive, hands-on tutorial designed to demystify what an API is and how it works, right inside your n8n canvas. It uses a simple restaurant analogy to explain the core concepts: You* are the "Client" (an *HTTP Request** node). The Kitchen is the "Server" (a Webhook node). The API is the Menu and the Waiter—the set of rules for how you can ask for things and get a response. The workflow is a series of self-contained lessons. Each lesson pairs an HTTP Request node (the customer placing an order) with a Webhook node (the kitchen receiving and responding to the order) to demonstrate a key concept: The Basics: Making a simple GET request to a URL. Customizing: Using Query Parameters to filter or modify your request. Sending Data: Using the POST method and a Body to send information to the server. Identification: Using Headers and simple Authentication to prove who you are. Handling Delays: Understanding how Timeouts prevent your workflow from getting stuck. Set up steps Setup time: < 1 minute This workflow is a self-contained tutorial and requires no external services or credentials. You may want to check the Base URL. Click "Execute Workflow" to run the entire tutorial. Follow the flow from top to bottom, exploring each "Lesson". For each lesson, click on the HTTP Request node and its corresponding Webhook node to see how they are configured and what they do. Read the sticky notes next to each lesson—they contain the core explanations! That's it! Explore and have fun learning the fundamentals of APIs in an interactive way.