by Jimleuk
This n8n workflow demonstrates how to manage your Qdrant vector store when there is a need to keep it in sync with local files. It covers creating, updating and deleting vector store records ensuring our chatbot assistant is never outdated or misleading. Disclaimer This workflow depends on local files accessed through the local filesystem and so will only work on a self-hosted version of n8n at this time. It is possible to amend this workflow to work on n8n cloud by replacing the local file trigger and read file nodes. How it works A local directory where bank statements are downloaded to is monitored via a local file trigger. The trigger watches for the file create, file changed and file deleted events. When a file is created, its contents are uploaded to the vector store. When a file is updated, its previous records are replaced. When the file is deleted, the corresponding records are also removed from the vector store. A simple Question and Answer Chatbot is setup to answer any questions about the bank statements in the system. Requirements A self-hosted version of n8n. Some of the nodes used in this workflow only work with the local filesystem. Qdrant instance to store the records. Customising the workflow This workflow can also work with remote data. Try integrating accounting or CRM software to build a managed system for payroll, invoices and more. Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/189F1fNOiw6naNSlSwnyLVEm_Ho_IFfdM/view?usp=sharing
by Keith Rumjahn
Case Study I'm too lazy to record every transaction for my expense tracking. Since all my expenses are digital, I just extract the transactions from bank PDF statements and screenshots into CSV to import into my budgeting software. Read more -> How I used A.I. to track all my expenses What this workflow does Upload your PDF or screenshots into Google Drive It then passes the PDF/image to Vertex Gemini to do some A.I. image recognition It then sends the transactions as CSV and stores it into another Google Drive folder Setup Set up 2 google drive folders. 1 for uploading and 1 for the output. Input your Google Drive crendtials Input your Vertex Gemini credentials How to adjust it to your needs You can upload other types of documents for information extraction. You can extract any text data from any image or PDF You can adjust the A.I. prompt to do different things
by David Ashby
🛠️ CircleCI Tool MCP Server Complete MCP server exposing all CircleCI 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 CircleCI Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n CircleCI Tool tool with full error handling 📋 Available Operations (3 total) Every possible CircleCI Tool operation is included: 🔧 Pipeline (3 operations) • Get a pipeline • Get many pipelines • Trigger a pipeline 🤖 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 CircleCI 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 CircleCI 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 Niklas Hatje
Use Case This workflow is beneficial when you're automatically adding new leads to your Pipedrive CRM. Usually, you'd have to manually review each lead to determine if they're a good fit. This process is time-consuming and increases the chances of missing important leads. This workflow ensures every new lead is promptly evaluated upon addition. What this workflow does The workflow runs every 5 minutes. On every run, it checks your new Pipedrive leads and enriches them with Clearbit. It then marks items as enriched and checks if the company of the new lead matches certain criteria (in this case if they are B2B and have more than 100 employees) and sends a Slack alert to a channel for every match. Pre Conditions You must have Pipedrive, Clearbit, and Slack accounts. You also need to set up the custom fields Domain and Enriched at in Pipedrive. Setup Go to Company Settings -> Data fields -> Organization and add Domain as a custom field Go to Company Settings -> Data fields -> Leads and add Enriched at as a custom date field Add your Pipedrive, Clearbit and Slack credentials. Fill the setup node below. To get the ID of your custom domain fields, simply run the Show only custom organization fields and Show only custom lead fields nodes below and copy the keys of your domain, and enriched at fields. How to adjust this workflow to your needs Modify the criteria to suit your definition of an interesting lead. If you only want to focus on interesting leads in Pipedrive, add a node that archives all others. This workflow was built using n8n version 1.29.1
by Ranjan Dailata
Who this is for The Real Estate Intelligence Tracker is a powerful automated workflow designed for real estate analysts, investors, proptech startups, and market researchers who need to collect and analyze structured data from real estate listings across the web at scale. This workflow is tailored for: Real Estate Analysts** - Tracking property prices, locations, and market trends Investment Firms** - Sourcing high-opportunity listings for portfolio decisions PropTech Developers** - Automating listing insights for SaaS platforms Market Researchers** - Extracting insights from competitive housing data Growth Teams** - Monitoring geographic property trends and pricing fluctuations What problem is this workflow solving? Collecting structured real estate listing data from property websites is difficult due to bot protections and unstructured HTML content. Manual data collection is slow and error-prone, and traditional scrapers often get blocked or miss context. This workflow solves: Automated bypass of anti-bot protection using Bright Data Web Unlocker Conversion of unstructured HTML content into clean text using a Markdown-to-text LLM pipeline Structured extraction of key listing data like price, location, property type, and features using OpenAI Aggregation and delivery of insights to Google Sheets, local storage, and webhook-based alerts What this workflow does Convert to Text: Transforms scraped HTML/markdown into clean text using a Basic LLM Chain Structured Data Extraction: Uses OpenAI GPT-4o with the Information Extractor node to parse property attributes (price, address, area, type, etc.) Aggregate & Merge: Combines data from multiple pages or listings into a cohesive structure Outbound Data Handling: Google Sheets** – Appends the structured real estate data for further analysis Save to Disk** – Persists structured JSON/text data locally Webhook Notification** – Sends data alerts or summaries to any third-party platform Pre-conditions You need to have a Bright Data account and do the necessary setup as mentioned in the "Setup" section below. You need to have an OpenAI Account. 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. In n8n, Configure the Google Sheet Credentials with your own account. Follow this documentation - Set Google Sheet Credential In n8n, configure the OpenAi account credentials. Ensure the URL and Bright Data zone name are correctly set in the Set URL, Filename and Bright Data Zone node. Set the desired local path in the Write a file to disk node to save the responses. How to customize this workflow to your needs Target Multiple Sites or Locations Update the Bright Data URL node dynamically with a list of regional real estate websites Loop through different city/state filter URLs Customize Extracted Fields Modify the Information Extractor prompt to extract fields like: Property size, number of bedrooms/bathrooms Days on market Nearby amenities or schools Agent contact details Integrate with More Destinations Add nodes to export data to Notion, Airtable, HubSpot, or your custom database Generate automated reports using PDF generators and email them Data Quality and Logging Add validation checks (e.g., missing price or address) Save intermediate files (markdown, raw HTML, JSON output) to disk for audit purposes
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.
by Nazmy
Based on Jonathan & Solomon work. > The only addition I've made is a Set node. This node organizes workflows into subfolders within the GitHub repository based on their respective tags. How it works This workflow will backup your workflows to GitHub. It uses the n8n API node to export all workflows. It then loops over the data, checks in GitHub to see if a file exists that uses the credential's ID. Once checked it will: update the file on GitHub if it exists; create a new file if it doesn't exist; ignore if it's the same. Who is this for? People wanting to backup their workflows outside the server for safety purposes or to migrate to another server.
by Intuz
This n8n template delivers a complete AI-powered solution for automated LinkedIn posts, including unique content, custom images, and optimized hashtags. Use cases are many: Generate and schedule tailored LinkedIn content for different use-cases. By feeding the AI specific prompts, you can create specific post depending upon the topics and visuals to maintain a consistency yet and an online presence. How it works Maintaining a consistent and engaging presence on LinkedIn can be time-consuming, requiring constant ideation, content creation, and manual posting. This workflow takes that burden off your shoulders, delivering a fully automated solution for generating and publishing high-quality LinkedIn content. Scheduled Content Engine: Each day (or on your chosen schedule), the workflow kicks into gear, ensuring a fresh stream of content. Smart Topic & Content Generation: Using the power of Google Gemini, it intelligently crafts unique content topics and then expands them into full, engaging posts, ensuring your message is always fresh and relevant. Dynamic Image Creation: To make your posts stand out, the workflow leverages an AI image generator (like DALL-E) to produce a custom, eye-catching visual that perfectly complements your generated text. SEO-Optimized Hashtag Generation: Google Gemini then analyzes your newly created post and automatically generates a set of relevant, trending, and SEO-friendly hashtags, significantly boosting your content's reach and discoverability. Seamless LinkedIn Publishing: Finally, all these elements—your compelling text, unique image, and powerful hashtags—are merged and automatically published to your LinkedIn profile, establishing you as a thought leader with minimal effort. How to Use: Quick Start Guide This guide will get your AI LinkedIn Content Automation workflow up and running in n8n. Import Workflow Template: Download the template's JSON file and import it into your n8n instance via "File" > "Import from JSON." Configure Credentials: Google Gemini: Set up and apply your API key credentials to all "Google Gemini Chat Model" nodes. AI Image Generation (e.g., OpenAI): Create and apply API key credentials for your chosen image generation service to the "Generate an Image" node. LinkedIn: Set up and apply OAuth credentials to the "Create a post" node for your LinkedIn account. Customize Schedule & AI Prompts: Schedule Trigger: Double-click "Schedule Trigger 1" to set how often your workflow runs (e.g., daily, weekly). AI Prompts: Review and edit the prompts within the "Content Topic Generator," "Content Creator," and "Hashtag Generator / SEO" nodes to guide the AI for your desired content style and topics. Test & Activate: Test Run: Click "Execute Workflow" to perform a test run and verify all steps are working as expected. Activate: Once satisfied, toggle the workflow "Active" switch to enable automated posting on your defined schedule. Requirements To use this workflow template, you will need: n8n Instance: A running n8n instance (cloud or self-hosted) to import and execute the workflow. Google Gemini Account: For content topic generation, content creation, and hashtag generation (requires Google Gemini API Key) from Google AI Studios. AI Image Generation Service Account: For creating images (e.g., OpenAI DALL-E API Key or similar service that the "Generate an Image" node uses). LinkedIn Account: For publishing the generated posts (requires LinkedIn OAuth Credentials for n8n connection). Connect with us Website: https://www.intuz.com/cloud/stack/n8n Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz
by David Ashby
Complete MCP server exposing 3 IPQualityScore 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 IPQualityScore 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 IPQualityScore 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://ipqualityscore.com/api • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (3 total) 🔧 Json (3 endpoints) • GET /json/email/{YOUR_API_KEY_HERE}/{USER_EMAIL_HERE}: Email Validation • GET /json/phone/{YOUR_API_KEY_HERE}/{USER_PHONE_HERE}: Phone Validation • GET /json/url/{YOUR_API_KEY_HERE}/{URL_HERE}: Malicious URL Scanner 🤖 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 IPQualityScore 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 simonscrapes
Use Case Research search engine rankings for SEO analysis: You need to track keyword rankings for your website You want to analyze competitor positions in search results You need data for SEO competition analysis You want to monitor SERP changes over time What this Workflow Does The workflow uses ScrapingRobot API to fetch Google search results: Retrieves SERP data for your target keywords Captures URL rankings and page titles Processes up to 5000 searches with free account Organizes results for SEO analysis Setup Create a ScrapingRobot account and get your API key Add your ScrapingRobot API key to the HTTP Request node's GET SERP token parameter Either connect your keyword database (column name "Keyword") or use the "Set Keywords" node Configure your preferred output database connection How to Adjust it to Your Needs Modify keyword source to pull from different databases Adjust the number of SERP results to capture Customize output format for your reporting needs More templates and n8n workflows >>> @simonscrapes
by David Ashby
🛠️ Twilio Tool MCP Server Complete MCP server exposing all Twilio 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 Twilio Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Twilio Tool tool with full error handling 📋 Available Operations (2 total) Every possible Twilio Tool operation is included: 🔧 Call (1 operations) • Make a call 🔧 Sms (1 operations) • Send an SMS/MMS/WhatsApp message 🤖 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 Twilio 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 Twilio 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
🛠️ Philips Hue Tool MCP Server Complete MCP server exposing all Philips Hue Tool operations to AI agents. Zero configuration needed - all 4 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 Philips Hue Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Philips Hue Tool tool with full error handling 📋 Available Operations (4 total) Every possible Philips Hue Tool operation is included: 🔧 Light (4 operations) • Delete a light • Get a light • Get many lights • Update a light 🤖 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 Philips Hue 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 Philips Hue 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.