Workflow Templates

Description Start your day with the perfect outfit suggestion tailored to the local weather. This workflow runs automatically every morning, fetches the current weather forecast for your city, and uses an AI stylist to generate a practical, gender-neutral outfit recommendation. It then designs a clean, vertical image card with all the details—date, temperature, weather conditions, and the complete outfit advice—and posts it directly to your Slack channel. It’s like having a personal stylist and weather reporter deliver a daily briefing right where your team communicates. Who’s it for Teams working in a shared office location who want a fun, daily update. Individuals looking to automate their morning routine and take the guesswork out of getting dressed. Community managers wanting to add engaging, automated content to their Slack workspace. Anyone interested in a practical example of combining weather data, AI, and dynamic image generation. How it works / What it does Triggers Daily: The workflow automatically runs every day at 6 AM. Fetches Weather: It gets the current weather forecast for a specified city (default is Tokyo) using the OpenWeatherMap node. Consults AI Stylist: The weather data is sent to an AI model, which acts as a stylist and returns a practical, gender-neutral outfit suggestion. Designs an Image Card: It dynamically creates a vertical image and writes the date, detailed weather info, and the AI's full recommendation onto it. Posts to Slack: Finally, it uploads the completed image card to your designated Slack channel with a friendly morning greeting. Requirements An n8n instance. An OpenWeatherMap API Key. An OpenRouter API Key (or credentials for another compatible AI model). A Slack workspace and the necessary permissions to connect an app. How to set up Set Weather Location: In the Get Weather Data node, add your OpenWeatherMap API Key and change the city name if you wish. Configure AI Model: In the OpenRouter Chat Model node, add your API Key. Configure Slack: In the Upload a file node, add your Slack credentials and, most importantly, select the channel where you want the forecast to be posted. Adjust Schedule (Optional): You can change the trigger time in the Daily 6AM Trigger node. How to customize the workflow Change the AI's Personality: Edit the system message in the Generate Outfit Advice node. You could ask the AI to be a pirate, a 90s fashion icon, or a formal stylist. Customize the Image: In the Create Image Card node, you can change the background color, font sizes, colors, and the layout of the text. Use a Different Platform: Swap the Slack node for a Discord, Telegram, or Email node to send the forecast to your preferred platform.

How it works Input: Google Sheets provides “Expected Content” rows (one per block/section). HTML Parse:** A JS/HTML step extracts Actual Content from the email’s HTML (from Gmail or any provided HTML source). Merge:** Expected and Actual items are merged into aligned pairs for comparison. Compare:** A JS node compares strings and produces a Result (Pass/Fail). (This flow intentionally stops at the result and does not compute a mismatch reason.) Log:** The workflow writes back “Actual Content” + “Result” to Google Sheets for reporting. Setup steps Google Sheets** Create a sheet with columns: SectionId, ExpectedContent, ActualContent, Result. Populate SectionId + ExpectedContent for each content block you want to verify. Email HTML source** Use a Gmail node to pull message HTML or use HTTP Request/Read Binary File + HTML/JS to supply the HTML. Extraction logic (JS/HTML)** Implement selectors/XPaths/DOM parsing for each SectionId to extract Actual Content. Normalize whitespace and trim HTML entities for a fair comparison. Merge & Compare** Merge on SectionId to align Expected ↔ Actual. In the Code (JS) node, compare strings and set Result to Pass if equal (or meets your rule), otherwise Fail. Write back** Use Google Sheets to update ActualContent and Result for each row. Requirements n8n with access to: Google Sheets, Code/HTML, and (optionally) Gmail nodes. A Google Sheets document with at least these columns: SectionId (or Key) ExpectedContent ActualContent (output) Result (output: Pass/Fail) Access to the email HTML (Gmail node, HTTP fetch, or paste‑in).

Odoo CRM MCP Server Workflow 📖 Overview This workflow connects an AI Agent with Odoo CRM using the Model Context Protocol (MCP). It allows users to manage CRM data in Odoo through natural language chat commands. The assistant interprets the user’s request, selects the appropriate Odoo action, and executes it seamlessly. 🔹 Key Features Contacts Management**: Create, update, delete, and retrieve contacts. Opportunities Management**: Create, update, delete, and retrieve opportunities. Notes Management**: Create, update, delete, and retrieve notes. Conversational AI Agent**: Understands natural language and maps requests to Odoo actions. Model Used**: OpenAI Chat Model. This makes it easy for end-users to interact with Odoo CRM without needing technical commands—just plain language instructions. ▶️ Demo Video Watch the full demo here: 👉 YouTube Demo Video ⚙️ Setup Guide Follow these steps to set up and run the workflow: 1. Prerequisites An Odoo instance configured with CRM enabled. An n8n or automation platform account where MCP workflows are supported. An OpenAI API key with access to GPT models. MCP Server installed and running. 2. Import the Workflow Download the provided workflow JSON file. In your automation platform (n8n, Langflow, or other MCP-enabled tool), choose Import Workflow. Select the JSON file and confirm. 3. Configure MCP Server Go to your MCP Server Trigger node in the workflow. Configure it to connect with your Odoo instance. Set API endpoint. Provide authentication credentials (API key). Test the connection to ensure the MCP server can reach Odoo. 4. Configure the OpenAI Model Select the OpenAI Chat Model node in the workflow. Enter your OpenAI API Key. Choose the model (e.g., gpt-5 or gpt-5-mini). 5. AI Agent Setup The AI Agent node links the Chat Model, Memory, and MCP Client. Ensure the MCP Client is mapped to the correct Odoo tools (Contacts, Opportunities, Notes). The System Prompt defines assistant behavior—use the tailored system prompt provided earlier. 6. Activate and Test Turn the workflow ON (toggle Active). Open chat and type: "Create a contact named John Doe with email john@example.com." "Show me all opportunities." "Add a note to John Doe saying 'Follow-up scheduled for Friday'." Verify the results in your Odoo CRM. ✅ Next Steps Extend functionality with Tasks, Stages, Companies, and Communication Logs for a complete CRM experience. Add confirmation prompts for destructive actions (delete contact/opportunity/note). Customize the AI Agent’s system prompt for your organization’s workflows.

Generate market research reports from news and competitor sites to Notion and Slack This workflow automates market research and competitive intelligence by collecting industry news and competitor website updates, analyzing them with AI, and publishing structured insights to Notion and Slack. It replaces manual monitoring and summarization with a repeatable, scalable workflow suitable for daily or weekly use. Who’s it for Marketing teams** who want to track industry trends and competitor messaging in one place Product managers** looking for early signals to inform roadmap and prioritization decisions Founders and analysts** who need automated market briefings without manual research How it works A scheduled trigger starts the workflow (daily by default). Industry news is fetched via NewsAPI while competitor websites are scraped in parallel. All collected content is consolidated and sent to OpenAI (GPT-4o) for analysis. The AI generates a structured report including trends, SWOT insights, and recommended actions. The full Markdown report is saved to a Notion database, and an executive summary is posted to Slack. If any API call or scraping step fails, an error notification is sent to Slack. How to set up Add API credentials for OpenAI, NewsAPI, Notion, and Slack. Configure keywords and competitor URLs in the Research Configuration node. Select your Notion database and Slack channels in the relevant nodes. Requirements OpenAI API key (GPT-4o access) NewsAPI account Notion and Slack accounts How to customize the workflow Change the trigger to run weekly or on demand Modify the AI prompt to focus on pricing, features, or specific competitors Add additional sources such as RSS feeds or more competitor sites

Introduction Automates AI-driven assignment grading with HTML and CSV output. Designed for educators evaluating submissions with consistent criteria and exportable results. How It Works Webhook receives papers, extracts text, prepares data, loads answers, AI grades submissions, generates results table, converts to HTML/CSV, returns response. Workflow Template Webhook → Extract Text → Prepare Data → Load Answer Script → AI Grade (OpenAI + Output Parser) → Generate Results Table → Convert to HTML + CSV → Format Response → Respond to Webhook Workflow Steps Input & Preparation: Webhook receives paper, extracts text, prepares data, loads answer script. AI Grading: OpenAI evaluates against answer key, Output Parser formats scores and feedback. Output & Response: Generates results table, converts to HTML/CSV, returns multi-format response. Setup Instructions Trigger & Processing: Configure webhook URL, set text extraction parameters. AI Configuration: Add OpenAI API key, customize grading prompts, define Output Parser JSON schema. Prerequisites OpenAI API key Webhook platform n8n instance Use Cases University exam grading Corporate training assessments Customization Modify rubrics and criteria Add PDF output Integrate LMS (Canvas, Blackboard) Benefits Consistent AI grading Multi-format exports Reduces grading time by 90%

Event Sponsor Matching: Google Sheets, GPT-4o & Gmail Revenue Optimizer Who is this for? Event planners, conference organizers, non-profits, and partnership managers who manage sponsor spreadsheets and want AI-powered package recommendations to maximize revenue. What problem is this workflow solving? Sponsor matching is manual and suboptimal: Hours matching 50+ sponsors to Gold/Silver/Bronze packages Missing perfect fits (enterprise → Gold, startups → Silver) No personalized outreach or tracking Revenue leaks from mismatched proposals This workflow auto-matches sponsors to optimal packages and emails owners instantly. What this workflow does Trigger**: Google Sheets update (Sponsors + Packages tabs) AI Matching: GPT-4o scores sponsors → **best 1-3 packages (budget/industry fit) Gmail Outreach**: "AI recommends Gold Package for TechCorp ($5k revenue, enterprise perfect fit)" Tracking Log**: Sheets append matches + scores + status Bonus**: Revenue projections by tier acceptance rates Setup (5 minutes) Google Sheets**: 2 tabs (Sponsors: Name/Industry/Budget/Goals + Packages: Tier/Price/Benefits) AI**: OpenAI API key (GPT-4o recommended) Email**: Gmail credentials (no hardcoded IDs—env vars) Configurable**: All via variables, scales to 1000s Fully configurable, no code changes needed. How to customize to your needs Packages**: Add Platinum/Diamond tiers or custom benefits Scoring**: Adjust GPT criteria (budget weight, industry focus) Outreach**: Swap Gmail for Outreach/Reply.io sequences Tracking**: HubSpot/Salesforce sync for closed deals Triggers**: Schedule daily or webhook for real-time ROI: 20% higher sponsor conversion** via perfect-fit recs 5x faster matching** (minutes vs hours) Revenue optimization** (proven enterprise events) Zero manual spreadsheet work** Need help customizing?: Contact me for consulting and support: LinkedIn / Message Keywords: sponsor matching, event sponsorship, conference revenue optimization, sponsor scoring, package matching, sponsorship outreach.

This N8N Template shows you how to create a basic Reddit scraper and email yourself the highest scoring threads This is for founders, service providers and anyone who wants to do more social listening but doesn't want to pay for an expensive tool. It uses a basic google sheet for configuration so you can manage and filter without updating any code. How it works We start with a scheduler (but you could manually trigger if you want) We read in a google sheet with the configuration of which subreddits you want to search, as well as minimum scoring so you can weight importance of each subreddit. Then you use an RSS feed to get the content Next, we normalize the RSS feed so that we can extract the important information Then we go back to the Google sheet (this time a different tab) that has the keywords we want to look for. We also include key words we don't want. We score each post based on the key words and additional pain points written into the scoring node. Then we filter out the posts that don't score high enough, or that we've already "seen" We keep track of the posts we've seen in another tab in the excel sheet. This prevents duplication Then we create the email, sending just the title as a link and send it via SMTP Requirements Google sheets account & credentials Google sheet with Email for SMTP How to Customize Create your own Google Sheets Template like this: Google Doc Template In the scoring node, update with painpoints (this could be added to Google Sheet config if you want) Update weights and scoring metrics in scoring node Update with your email

Telegram Voice → AI Summary & Sentiment Analysis via Gmail This n8n template demonstrates how to capture Telegram voice messages, transcribe them into text using AssemblyAI, analyze the transcript with AI for summary and sentiment insights, and finally deliver a structured email report via Gmail. Use cases Automating meeting or lecture voice note transcriptions. Gathering student feedback or training session insights from voice messages. Quickly summarizing Telegram-delivered audio inputs into structured reports. Reducing manual effort in capturing sentiment and key action items from conversations. How it works A voice message is sent to a connected Telegram Bot. The workflow fetches the file and uploads it to AssemblyAI. AssemblyAI generates a transcript from the audio. The transcript is analyzed by OpenAI to extract: Executive summary (120–180 words) Sentiment label and score Key points Action items (if any) Notable quotes Topics The formatted analysis is sent as an email report using Gmail. The workflow ends with a clean summary email containing actionable insights. How to use Import this workflow into your n8n instance. Set up and connect the required credentials: Telegram Bot API token AssemblyAI API key OpenAI API key Gmail OAuth2 account Replace placeholders (e.g., <<YOUR_EMAIL ID>> and <<YOUR_ASSEMBLYAI_API_KEY>>) with your actual values. Start the workflow. Whenever a voice message is received on the Telegram Bot, the workflow will process it end-to-end and deliver a polished email report. Requirements Telegram Bot account (API token) AssemblyAI account with API key OpenAI account with API key Gmail OAuth2 credentials configured in n8n Active n8n instance Customising this workflow You can customize the email formatting, sentiment thresholds, or extend the workflow to save transcripts into Google Drive, Airtable, or any other connected apps. Additionally, you can trigger the same workflow from multiple input sources (e.g., local audio files, Google Drive links, or Telegram).

Who is this for? Businesses and developers who want to automate customer support or engagement on Facebook Messenger using AI-powered responses. What does it do? Creates an intelligent Facebook Messenger chatbot that: Responds to messages using OpenAI (gpt-4o-mini) Batches rapid-fire messages into a single AI request Maintains conversation history (50 messages per user) Shows professional UX feedback (seen indicators, typing bubbles) How it works Webhook Verification - Handles Facebook's GET verification request Message Reception - Receives incoming messages via POST webhook Message Batching - Waits 3 seconds to collect multiple quick messages AI Processing - Sends combined message to OpenAI with conversation context Response Delivery - Formats and sends the AI response back to Messenger Setup Configure Facebook Graph API credential with your Page Access Token Configure OpenAI API credential with your API key Set your verify token in the "Is Token Valid?" node Register the webhook URL in Facebook Developer Console Key Features Message Batching: Combines "Hey" + "Can you help" + "with my order?" into one request Conversation Memory: Remembers context from previous messages Echo Filtering: Prevents responding to your own messages Response Formatting: Cleans markdown for Messenger's 2000-char limit

Who's it for This workflow is for anyone who wants to stay informed without the overwhelm. Whether you're tracking industry news, following your favorite blogs, monitoring competitors, or just keeping up with topics you care about—this automated newsletter keeps you in the loop effortlessly. What it does This automated workflow fetches content from your favorite RSS feeds, filters it based on your interests using Google Gemini AI, and sends you a beautifully formatted HTML newsletter at your preferred time. The AI selects the top 10-15 items from each category based on keywords you define, delivering only what matters to you. How it works Schedule Trigger: Runs daily at your chosen time (default: 9:00 AM) RSS Feeds: Fetches content from your favorite news sources and websites Processing: Splits URLs, loops through feeds in batches to avoid rate limits Merge & Convert: Combines all RSS items into a single CSV file AI Curation: Google Gemini analyzes the content and selects relevant items based on your keywords Email Delivery: Sends a personalized HTML newsletter with summaries and images Requirements Google Gemini API** credentials (for AI curation) SMTP credentials** (for sending emails) Active n8n instance (self-hosted or cloud) How to set up Add your Google Gemini API credentials in both Gemini nodes Configure your SMTP settings in the "Send email" node Update the email addresses (from and to) in the email node Add your favorite RSS feed URLs in the "Set" nodes Customize the AI keywords in "Analyze document" to match your interests Set your preferred schedule time in the trigger node How to customize Add your RSS feeds**: Replace the example URLs in both "Set" nodes with RSS feeds from your favorite sources (blogs, news sites, podcasts, YouTube channels, etc.) Define your interests**: Modify the keywords in the "Analyze document" AI prompt to filter content that matters to you Adjust categories**: Change the two sections to match your needs (e.g., "Industry News" and "Competitor Updates" or "Learning Resources" and "Tools") Change email format**: Update the HTML template in the AI prompt to customize the newsletter design Modify delivery time**: Update the schedule trigger to run at your preferred time

🟢 Manual Trigger Workflow starts manually to initiate the reconciliation process on demand. 📄 Fetch Invoices & Bank Statements Retrieves invoice data and bank statement data from Google Sheets for comparison. 🔀 Merge Data Combines both datasets into a single structured dataset for processing. 🧩 Format Payload for AI Function node prepares and structures the merged data into a clean JSON payload for AI analysis. 🤖 AI Reconciliation AI Agent analyzes the invoice and bank statement data to identify matches, discrepancies, and reconciled entries. 🧮 Parse AI Output Parses the AI response into a structured format suitable for adding back to Google Sheets. 📊 Update Sheets Adds the reconciled data and reconciliation results into the target Google Sheet for recordkeeping. 🧾 Prerequisites ✅ OpenAI API Credentials Required for the AI Reconciliation node to process and match transactions. Add your OpenAI API key in n8n → Credentials → OpenAI. ✅ Google Sheets Credentials Needed to read invoice and bank statement data and to write reconciled results. Add credentials in n8n → Credentials → Google Sheets. ✅ Google Sheets Setup The connected spreadsheet must contain the following tabs: Invoices – for invoice data Bank_Statement – for bank transaction data Reconciled_Data – for storing the AI-processed reconciliation output ✅ Tab Structure & Required Headers Invoices Sheet Columns: Invoice_ID Invoice_Date Customer_Name Amount Status Bank_Statement Sheet Columns: Transaction_ID Transaction_Date Description Debit/Credit Amount Reconciled_Data Sheet Columns: Invoice_ID Transaction_ID Matched_Status Remarks Confidence_Score ⚙️ n8n Environment Setup Ensure all nodes are connected correctly and the workflow has permission to access the required sheets. Test each fetch and write operation before running the full workflow.

How it works This workflow captures idea submissions from a webhook and enriches them using AI. It extracts key fields like Title, Tags, Submitted By, and Created date in IST format. The cleaned data is stored in a Notion database for centralized tracking. Finally, a confirmation message is posted in Slack to notify the team. Step-by-step Step-by-step 1. Capture and process submission Webhook** – Receives idea submissions with text and user ID. AI Agent & OpenAI Model** – Enrich and structure the input into Title, Tags, Submitted By, and Created fields. Code** – Extracts clean data, formats tags, and prepares the entry for Notion. 2. Store in Notion Add to Notion** – Creates a new database entry with mapped fields: Title, Submitted By, Tags, Created. 3. Notify in Slack Send Confirmation (Slack)** – Posts a confirmation message with the submitted idea title. Why use this? Centralizes idea collection directly into Notion for better organization. Eliminates manual formatting with AI-powered data structuring. Ensures consistency in tags, submitter info, and timestamps. Provides instant team-wide visibility via Slack notifications. Saves time while keeping idea management streamlined and transparent.