Workflow Templates

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.

Note: This workflow assumes you already have your product’s Amazon reviews saved in a Google Sheet. If you still need those reviews, run my Amazon Reviews Scraper workflow first, then plug the resulting spreadsheet into this template. What it does Transforms any draft Google Doc into multiple high-converting sales pages. It blends Alex Hormozi’s value-stacking tactics with persona targeting based on Maslow’s Hierarchy of Needs, using your own customer reviews for proof and voice of customer (VOC). Perfect for • Growth and creative strategists • Freelance copywriters and agencies • Founders sharpening offers and funnels Apps used Google Sheets, Google Docs, LangChain OpenRouter LLM How it works Form Trigger collects Drive folder IDs, base copy URL and options. Workflow fetches the draft copy and product feature doc. It samples reviews, extracts VOC insights and maps them to Maslow needs. LLM drafts headlines and hooks following Hormozi’s \$100M Offers principles. Personas drive tone, objections and urgency in each copy variant. Loop writes one Google Doc per variant in your chosen folder. Customer analysis docs are saved to a second folder for reuse. Setup Share two Drive folders, copy the IDs (text after folders/). Paste each ID into Customer Analysis Folder ID and Advertorial Copy Folder ID. Provide File Name, Base copy (Google Docs URL) and Product Feature/USPs Doc. Optional: Reviews Sheet URL, Number of reviews to use, Target City. Set Number of Copies you need (1–20). Add Google Docs OAuth2 and Google Sheets OAuth2 credentials in n8n. If you have any questions in running the workflow, feel free to reach out to me at my youtube channel: https://www.youtube.com/@lifeofhunyao

N8n recently introduced folders and it has been a big improvement on workflow management on top of the tags. This means the current workflows need to be moved manually to the folders. The simplest idea to try is to convert the current tags into folders and move all the current workflows within the respective tags into the folders This assumes the tag name will be used as the folder name. To Note For workflows that use more than 1 tag, the workflow will be assigned the last tag that runs as the folder. How does it work I took the liberty of simplifying the setup of this workflow that will be needed on your part and also be beginner-friendly Copy and paste this workflow into your n8n canvas. You must have existing workflows and tags before you can run this Set your n8n login details on the node set Credentials with the n8n URL, username, and password. Setup your n8n API credentials on the n8n node get workflows Run the workflow. This opens up a form where you can select the number of tags to move and click on submit The workflow responds with the successful number of workflows that were imported Read more about the template Built by Zacharia Kimotho - Imperol

This workflow leverages n8n to perform automated Google Maps API queries and manage data efficiently in Google Sheets. It's designed to extract specific location data based on a given list of ZIP codes and categories. Features Queries the Google Maps API for location data using predefined ZIP codes and subcategories. Filters, de-duplicates, and organizes data into structured rows in Google Sheets. Implements exponential backoff retries to handle API rate limits. Logs and updates statuses directly in Google Sheets for easy tracking. Prerequisites Google OAuth Credentials: A configured Google Cloud project for Google Maps API and Sheets API access. Google Sheets: A sheet with ZIP codes and categories defined (e.g., "AZ Zips"). n8n Setup: A running instance of n8n with credentials configured for Google OAuth. Setup Instructions 1. Prepare Google Sheets Add the ZIP codes to the "AZ Zips" sheet. Define subcategories in another sheet (e.g., "Google Maps Categories"). Provide the sheet's URL in the Settings node of the workflow. 2. Configure API Access Set up Google OAuth credentials for Maps and Sheets APIs in n8n. Ensure your API key has access to the places.searchText endpoint. 3. Workflow Customization Modify textQuery parameters in the GMaps API node to match your query needs. Adjust trigger intervals as required (e.g., manual or scheduled execution). 4. Run the Workflow Execute the workflow manually or schedule periodic runs to keep your data updated. Notes This workflow includes robust error handling to retry failed API calls with exponential backoff. All data is organized and logged directly in Google Sheets for easy reference and updates. For more information or issues, feel free to reach out!

Description This workflow automatically monitors companies across courts, regulators, and jurisdictions to detect legal risk signals early. It helps legal, compliance, and risk teams stay ahead of litigation threats without manually scanning dozens of public sources. Overview This workflow scrapes court records, regulatory filings, and legal news using Bright Data, then uses AI to classify, score, and cluster legal events by jurisdiction and topic. It filters noise, identifies high-risk cases, and generates executive-ready intelligence — including High-Risk Escalation Alerts and Litigation Monitoring Briefs — logged directly into Google Sheets dashboards. Tools Used n8n: The automation platform that orchestrates the workflow. Bright Data: For scraping court records, regulatory sources, and legal news without getting blocked. OpenRouter: For AI-powered legal case classification, risk scoring, and report generation. Google Sheets: For logging alerts, monitoring summaries, and error tracking. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data API credentials to the Bright Data node. Configure OpenRouter: Add your OpenRouter API key for AI classification and report generation. Set Up Google Sheets: Create a spreadsheet following the "Google Sheets Setup" sticky note inside the workflow, then connect each Google Sheets node to your document. Customize: Edit the configuration node to set your target companies, jurisdictions, courts, and regulators. Use Cases Corporate Legal Teams: Get early warnings on litigation involving your company or partners. M&A Due Diligence: Screen acquisition targets for hidden legal exposure before closing deals. Compliance Officers: Monitor regulatory actions across multiple jurisdictions in one place. Risk Analysts: Track litigation density patterns and jurisdiction concentration risks. Investor Relations: Surface legal threats that could impact portfolio companies or stock price. Connect with Me Website: https://www.nofluff.online YouTube: https://www.youtube.com/@YaronBeen/videos LinkedIn: https://www.linkedin.com/in/yaronbeen/ Get Bright Data: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #brightdata #webscraping #legalrisk #litigation #legaltech #riskmanagement #compliance #duediligence #legalmonitoring #courtrecords #regulatorymonitoring #corporatelegal #riskanalysis #litigationtracking #jurisdictionrisk #legalintelligence #n8nworkflow #workflow #nocode #businessintelligence #earlywarning #legalcompliance #riskassessment

Template Overview This template is designed for individuals and businesses who want to maintain a consistent presence on the Fediverse while also posting on Threads or managing multiple Fediverse profiles. By automating the process of resharing statuses or posts, this workflow saves time and ensures regular engagement across accounts. Use Case The template addresses the challenge of managing activity across Fediverse accounts by automatically boosting or resharing posts from a specific account to your own. It is especially helpful for users who want to consolidate engagement without manually reposting content across multiple platforms or profiles. How It Works The workflow runs on a scheduled trigger and retrieves recent posts from a specified Fediverse account, such as your Threads.net account. It uses a JavaScript filter to identify posts from the current day and then automatically boosts or reshares them to your selected Mastodon profile. Preconditions You need a Mastodon account with developer access. Identify a Threads.net or other Fediverse account which you want to boost. Basic familiarity with APIs and setting up credentials in n8n. Setup Steps Step 1: Create a Developer Application on Mastodon Log in to your Mastodon account and navigate to Preferences > Development > New Application. Fill out the required information and create your application. Set Scopes to atleast read, profile, write:statuses. Click Submit. Note down the access token generated for this application. Step 2: Get the Account ID Use the following command to retrieve the account ID for the profile you want to boost: curl -s "https://mastodon.social/api/v1/accounts/lookup?acct=<ACCOUNTNAME>" Alternatively, paste the URL into a GET node on n8n. From the returned JSON, copy the "id" field value (e.g., {"id":"110564198672505618", ...}). Step 3: Update the "Get Statuses" Node Replace <ACCOUNTID> in the URL field with the ID you retrieved in Step 2: https://mastodon.social/api/v1/accounts/<ACCOUNTID>/statuses Step 4: Configure the "Boost Statuses" Node Authentication type will already be set to Header Auth. Grab the access token from Step 1. In the Credential for Header Auth field, create a new credential. Click the pencil icon in the top-left corner to name your credential. In the Name field, enter Authorization. In the Value field, enter Bearer <YOUR_MASTODON_ACCESS_TOKEN>. (Note: there is a space after "Bearer.") Save the credential, and it should automatically be selected as your Header Auth. Step 5: Test the Workflow Run the workflow to ensure everything is set up correctly. Adjust filters or parameters as needed for your specific use case. Customization Guidance Replace mastodon.social with your own Mastodon domain if you're using a self-hosted instance. Adjust the JavaScript filter logic to meet your specific needs (e.g., filtering by hashtags or keywords). For enhanced security, store the access token as an n8n credential. Embedding it directly in the URL is ++not recommended++. Notes This workflow is designed to work with any Mastodon domain. Ensure your Mastodon account has appropriate permissions for boosting posts. By following these steps, you can automate your Fediverse engagement and focus on creating meaningful content while the workflow handles the rest!

Description This workflow is designed to automate the security reputation check of domains and IP addresses using multiple APIs such as VirusTotal, AbuseIPDB, and Google DNS. It assesses potential threats including malicious and suspicious scores, as well as email security configurations (SPF, DKIM, DMARC). The analysis results are processed by AI to produce a concise assessment, then automatically updated into Google Sheets for documentation and follow-up. How It Works Automatic Trigger – The workflow runs periodically via a Schedule Trigger. Data Retrieval – Fetches a list of domains from Google Sheets with status "To do". Domain Analysis – Uses VirusTotal API to get the domain report, perform a rescan, and check IP resolutions. IP Analysis – Checks IP reputation using AbuseIPDB. Email Security Validation – Verifies SPF, DKIM, and DMARC configurations via Google DNS. AI Assessment – Analysis data is processed by AI to produce a short summary in Indonesian. Data Update – The results are automatically updated to Google Sheets, changing the status to "Done" or adding notes if potential threats are found. How to Setup Prepare API Keys Sign up and obtain API keys from VirusTotal and AbuseIPDB. Set up access to Google Sheets API. Configure Credentials in n8n Add VirusTotal API, AbuseIPDB API, and Google Sheets OAuth credentials in n8n. Prepare Google Sheets Create a sheet with columns No, Domain, Customer, Keterangan, Status. Ensure initial data has the status "To do". Import Workflow Upload the workflow JSON file into n8n. Set Schedule Trigger Define the checking interval as needed (e.g., every 1 hour). Test Run Run the workflow manually to ensure all API connections and Google Sheets output work properly.

Try It Out! This n8n template demonstrates how to build an autonomous AI news agent using Decodo MCP that automatically finds, scrapes, and delivers fresh industry news to your team via Slack. Use cases are many – automated news monitoring for your industry, competitive intelligence gathering, startup monitoring, regulatory updates, research automation, or daily briefings for your organization. How it works Define your news topics using the Set node – AI, MCP, web scraping, whatever matters to your business. The AI Agent processes those topics using the Gemini Chat Model, determining which tools to use and when. Here's where it gets interesting: Decodo MCP gives your AI agent the tools to search Google, scrape websites, and parse content automatically – all while bypassing geo-restrictions and anti-bot measures. The agent hunts for fresh articles from the last 48 hours, extracts clean data, and returns structured JSON results. Format Results cleans up the AI's messy output and removes duplicates. Your polished news digest gets delivered to Slack with clickable links and summaries. How to use Schedule trigger runs daily at 9 AM – adjust timing or swap for webhook triggers as needed. Customize topics in the Set node to match your industry. Scales effortlessly: add more topics, tweak search criteria, done. Requirements Decodo MCP credentials (free trial available) – grab the Smithery connection URL with keys and paste it straight into your n8n MCP node. Done. Gemini API key for the AI processing – drop it into the Google Gemini Chat Model node and pick whichever Gemini model fits your needs. Slack workspace for delivery – n8n's Slack integration docs have you covered. What the final output looks like Here's what your team receives in Slack every morning: Need help? Join the Discord or email support@decodo.com for questions. Happy Automating!

AI-Powered SENSEX Signal Generator > Gemini, Yahoo Finance & Google Sheets This n8n workflow automatically analyzes SENSEX market data using technical indicators and AI (Google Gemini) to generate trading signals (Buy/Sell). It filters only high-confidence signals and logs them into Google Sheets for tracking. Quick Implementation Steps Import the workflow into your n8n account Add credentials: Google Gemini API Google Sheets OAuth2 Create a Google Sheet with columns: Date | Index | Signal | Confidence | Trend | Reason Execute the workflow manually Check results in your Google Sheet What It Does This workflow automates stock market signal generation for the SENSEX index using a hybrid approach that combines technical analysis and AI-based reasoning. First, it fetches historical market data from Yahoo Finance and computes key indicators such as moving averages, momentum, volatility and price change. These indicators help identify the current market trend and behavior. Next, it retrieves the latest SENSEX-related news headlines and feeds both the technical data and news into a Google Gemini AI model. The AI analyzes this combined input to generate a trading signal (Buy/Sell), along with confidence, strength, risk level and reasoning. Finally, the workflow calculates a score based on AI output, filters only high-quality signals (score > 70) and logs them into Google Sheets for further tracking and decision-making. Who It's For Traders looking for automated signal generation Developers building fintech or trading tools Data analysts interested in AI-driven market insights Automation enthusiasts using n8n Anyone exploring AI + financial data workflows Requirements To use this workflow, you need: n8n account (self-hosted or cloud) Google Gemini API credentials Google Sheets OAuth2 credentials A Google Sheet with predefined columns Internet access for: Yahoo Finance API Google News RSS How It Works & Setup Guide Workflow Breakdown Manual Trigger Starts the workflow execution manually Fetch Market Data HTTP Request pulls SENSEX data from Yahoo Finance Technical Analysis Code node calculates: 5-day & 20-day moving averages Momentum Volatility Price change (%) Data Structuring Set node formats key metrics for AI processing Fetch Latest News RSS node pulls SENSEX-related news from Google News Limit News Only the latest article is passed to AI AI Signal Generation Gemini AI analyzes: Technical indicators News sentiment Outputs: Signal (Buy/Sell) Confidence Strength Risk level Reason Parse AI Output Converts AI response into structured JSON Score Calculation Score is computed using: Confidence Strength Risk level Validation Only signals with score > 70 are accepted Store Results Valid signals are appended to Google Sheets Setup Instructions Import workflow into your n8n account Configure credentials: Google Gemini API Google Sheets OAuth2 Update Google Sheet ID (if needed) Verify API URLs: Yahoo Finance endpoint Google News RSS link Execute manually using Start node Check output in Google Sheets How To Customize Nodes HTTP Request Node** Change index (e.g., NIFTY, NASDAQ) by updating the URL Code Node (Indicators)** Modify moving average window (e.g., 10-day, 50-day) Add RSI, MACD, etc. AI Agent Prompt** Customize signal logic Add stricter risk rules or additional outputs Score Calculator** Adjust scoring weights: Confidence threshold Strength importance Risk penalties Google Sheets Node** Add more columns like: Risk Level Strength Score Add-ons (Enhancements) Add Cron Trigger for automation (daily execution) Integrate Telegram/Email alerts for signals Store data in a database (PostgreSQL, MongoDB) Add multi-index support (NIFTY, Dow Jones, etc.) Build a dashboard (Power BI / Streamlit) Include advanced indicators like RSI, MACD Use Case Examples Automated Trading Signal Logger Generate and store signals daily AI-Assisted Decision Support Use signals as guidance before trading Market Trend Monitoring System Track trend + volatility over time Fintech Product Prototype Build an AI-based trading assistant Research & Backtesting Tool Analyze historical signals and performance There can be many more use cases depending on how you want to extend this workflow. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|--------------|---------| | No data from Yahoo Finance | API URL incorrect or rate-limited | Verify endpoint and retry | | AI output not parsing | Invalid JSON from AI | Ensure prompt enforces strict JSON | | No rows in Google Sheets | Validation failed (score ≤ 70) | Check score logic or lower threshold | | Credential errors | Missing or incorrect API keys | Reconfigure credentials | | Empty news input | RSS feed issue | Verify RSS URL and connectivity | | Workflow stops early | Node misconfiguration | Check execution logs in n8n | Need Help? If you need assistance with: Setting up this workflow Customizing AI logic Adding new integrations (Telegram, dashboards, APIs) Scaling this into a production-ready system Feel free to reach out to n8n automation developers at WeblineIndia We can help you build powerful automation workflows tailored to your business needs.

Transform database design from weeks to minutes with this intelligent multi-agent system. Perfect for agencies, consultancies, and SaaS companies offering database architecture as a lead magnet or service. 🤖 4 Specialized AI Agents: Agent 1 (Architect):** Designs complete schema with tables, relationships, indexes Agent 2 (Reviewer):** Validates design for performance, security, scalability Agent 3 (Optimizer):** Adds advanced features and scores the design (0-100) Agent 4 (SQL Generator):** Creates production-ready migration scripts 🔄 Smart Quality Loop: Automatically retries up to 3 times if score falls below B grade, feeding previous feedback to improve the design iteratively. ✨ What You Get: Complete database schema (JSON) Comprehensive score card with letter grade Review feedback with severity levels (Critical/High/Medium/Low) Production-ready SQL migration script Optional auto-execution in PostgreSQL/MySQL Iteration count and optimization recommendations 💼 Perfect For: Digital agencies offering database design services SaaS companies needing rapid prototyping Consultancies creating lead magnets Developers modernizing legacy systems Startups validating data models 🎯 Use as Lead Magnet: Offer free database blueprints to capture leads, then upsell implementation, custom automations, and ongoing optimization services. ⚙️ Technical Highlights: Optimized temperature settings per agent (0.1-0.5) Claude Sonnet 4.5 for maximum quality Structured JSON output for easy integration Error handling and graceful degradation Execution time: 60-90 seconds average Cost: ~$0.15-0.30 per run Use Cases Agency Lead Magnet Capture leads by offering free database architecture reviews and blueprints Rapid Prototyping Quickly generate database schemas for MVP development and validation Legacy System Modernization Help companies redesign outdated database structures with modern best practices Technical Consulting Provide instant database assessments and recommendations to clients Educational Tool Teach database design principles through AI-generated examples and feedback Pre-Sales Tool Demonstrate technical expertise to prospects before engagement Key Features ✅ Multi-agent AI collaboration with specialized roles ✅ Automatic quality control and iterative improvement (max 3 retries) ✅ Support for PostgreSQL, MySQL, MSSQL, MariaDB ✅ Production-ready SQL script generation ✅ Comprehensive scoring system (Schema/Performance/Scalability/Security) ✅ Optional automatic SQL execution ✅ Detailed feedback with actionable recommendations ✅ Customizable form fields for different industries ✅ Error handling and graceful failures ✅ Complete audit trail of all agent decisions Setup Instructions PREREQUISITES: Anthropic API key (Claude Sonnet 4.5 access) PostgreSQL/MySQL database (optional, for auto-execution) n8n version 1.0+ with LangChain nodes CONFIGURATION STEPS: Import the workflow JSON into your n8n instance Configure Anthropic API credentials: Add your Anthropic API key in n8n credentials Connect all 4 AI model nodes to your credential (Optional) Configure database connection: In "Execute SQL in PostgreSQL" node, add your database credentials Use a TEST/SANDBOX database, never production Or disable this node if you prefer manual execution Customize the form (optional): Edit form fields in "On form submission" node Add industry-specific questions Adjust required fields based on your needs Test the workflow: Use the form URL to submit a test request Check execution time and quality Verify all agents are responding correctly Customize agent prompts (optional): Adjust system messages for industry-specific requirements Modify scoring criteria in Agent 3 Add custom validation rules in Agent 2 Deploy: Share the form URL as your lead magnet Embed in website or landing pages Set up email notifications for submissions COST CONSIDERATIONS: Each execution costs ~$0.15-0.30 in API calls Failed attempts (retries) increase cost Consider rate limiting for public forms Requirements REQUIRED: Anthropic API Key (Claude access) n8n version 1.0+ LangChain nodes enabled OPTIONAL: PostgreSQL/MySQL database connection (for auto-execution) Email service (for result delivery) CRM integration (for lead capture) Tags #ai-agents #database-design #postgresql #mysql #lead-generation #automation #langchain #claude #schema-design #multi-agent #consulting-tool #saas-tool #development #code-generation #sql-generator 📖 Website: https://evervise.ai/ ✨ Support: mark.marin@evervise.com N8N Link

Quick overview This workflow fetches the latest blog post from an RSS feed, uses DeepSeek to generate 5-slide carousel copy, creates AI background images with fal.ai, builds a PDF carousel in Posta, and publishes the post to LinkedIn via a connected Posta social account. How it works Starts when you manually execute the workflow. Reads your blog’s RSS feed, sorts items by publish date, and selects the newest post. Sends the post title and content to DeepSeek (via an LLM chain) to generate minified JSON containing a caption, tags, and five slides with titles, bodies, and image prompts. Splits the slide list into individual items, applies a theme color, and generates a square background image for each slide with fal.ai. Downloads each generated image and uploads it to Posta as media, then re-associates the uploaded media IDs with the corresponding slide text. Uses Posta to render the slides into a text carousel PDF, then publishes the PDF to the selected LinkedIn account with the generated caption and hashtags. Setup Add your Posta API credential, select the target LinkedIn social account ID, and update any fixed values like the logoMediaId used for the PDF. Add your DeepSeek API credential and confirm the LLM output stays valid minified JSON for the parser. Add your fal.ai API credential and adjust the image generation prompt or theme_color value to match your brand. Replace the RSS feed URL with your blog feed and confirm the feed provides title and content fields (for example, content:encoded). Additional info Video explanation: https://youtu.be/CC-_i6LanLg

Quick overview Youtube Video: https://youtu.be/kO4LgKT6oME?si=VpUEz2LKuxMujrUp This workflow receives WhatsApp messages, checks the sender in HighLevel, and uses Google Gemini with Redis chat memory to collect shipment details, then requests an LTL quote from the Warp API, applies a commission, and replies with either a conversational prompt or a final freight quote. How it works Receives an incoming WhatsApp message and only continues when the text body is not empty. Looks up the sender’s phone number in HighLevel and stops contacts marked as Do Not Disturb from being processed further. Uses a Google Gemini-powered agent with Redis chat memory to ask for missing contact and freight details in a fixed order, optionally creating the HighLevel contact or marking the lead as DND when the user opts out. Parses the agent’s structured JSON output and checks whether the required shipment data collection is complete. If data is incomplete, sends the agent’s conversational reply back to the user via WhatsApp. If data is complete, posts the shipment details to the Warp LTL quote API, adds a configured commission percentage to the returned price, and sends the finalized quote back to the user via WhatsApp. Setup Connect WhatsApp credentials for both the WhatsApp Trigger and WhatsApp “send message” actions, and configure the webhook in Meta/WhatsApp so inbound messages reach this workflow. Add a HighLevel OAuth2 credential and confirm your HighLevel account has permission to search contacts, create contacts, and update the DND field. Add a Google Gemini (PaLM) API credential and a Redis credential for chat memory, and ensure Redis is reachable from your n8n instance. Add an HTTP Header Auth credential for the Warp API and verify the quote endpoint URL, headers, and request body fields match your Warp account requirements. Adjust the commission percentage value (and any quoting assumptions like weight per pallet) to match your pricing policy.