Build your own N8N workflows MCP server
This n8n template shows you how to create an MCP server out of your existing n8n workflows. With this, any MCP client connected can get more done with powerful end-to-end workflows rather than just simple tools. Designing agent tools for outcome rather than utility has been a long recommended practice of mine and it applies well when it comes to building MCP servers; In gist, agents to be making the least amount of calls possible to complete a task. This is why n8n can be a great fit for MCP servers! This template connects your agent/MCP client (like Claude Desktop) to your existing workflows by allowing the AI to discover, manage and run these workflows indirectly. How it works An MCP trigger is used and attaches 4 custom workflow tools to discover and manage existing workflows to use and 1 custom workflow tool to execute them. We'll introduce an idea of "available" workflows which the agent is allowed to use. This will help limit and avoid some issues when trying to use every workflow such as clashes or non-production. The n8n node is a core node which taps into your n8n instance API and is able to retrieve all workflows or filter by tag. For our example, we've tagged the workflows we want to use with "mcp" and these are exposed through the tool "search workflows". Redis is used as our main memory for keeping track of which workflows are "available". The tools we have are "add Workflow", "remove workflow" and "list workflows". The agent should be able to manage this autonomously. Our approach to allow the agent to execute workflows is to use the Subworkflow trigger. The tricky part is figuring out the input schema for each but was eventually solved by pulling this information out of the workflow's template JSON and adding it as part of the "available" workflow's description. To pass parameters through the Subworkflow trigger, we can do so via the passthrough method - which is that incoming data is used when parameters are not explicitly set within the node. When running, the agent will not see the "available" workflows immediately but will need to discover them via "list" and "search". The human will need to make the agent aware that these workflows will be preferred when answering queries or completing tasks. How to use First, decide which workflows will be made visible to the MCP server. This example uses the tag of "mcp" but you can all workflows or filter in other ways. Next, ensure these workflows have Subworkflow triggers with input schema set. This is how the MCP server will run them. Set the MCP server to "active" which turns on production mode and makes available to production URL. Use this production URL in your MCP client. For Claude Desktop, see the instructions here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/integrating-with-claude-desktop. There is a small learning curve which will shape how you communicate with this MCP server so be patient and test. The MCP server will work better if there is a focused goal in mind ie. Research and report, rather than just a collection of unrelated tools. Requirements N8N API key to filter for selected workflows. N8N workflows with Subworkflow triggers! Redis for memory and tracking the "available" workflows. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow If your targeted workflows do not use the subworkflow trigger, it is possible to amend the executeTool to use HTTP requests for webhooks. Managing available workflows helps if you have many workflows where some may be too similar for the agent. If this isn't a problem for you however, feel free to remove the concept of "available" and let the agent discover and use all workflows!
By JimleukNamesilo bulk domain availability checker
Introduction The namesilo Bulk Domain Availability workflow is a powerful automation solution designed to check the registration status of multiple domains simultaneously using the Namesilo API. This workflow efficiently processes large lists of domains by splitting them into manageable batches, adhering to API rate limits, and compiling the results into a convenient Excel spreadsheet. It eliminates the tedious process of manually checking domains one by one, saving significant time for domain investors, web developers, and digital marketers. The workflow is particularly valuable during brainstorming sessions for new projects, when conducting domain portfolio audits, or when preparing domain acquisition strategies. By automating the domain availability check process, users can quickly identify available domains for registration without the hassle of navigating through multiple web interfaces. Who is this for? This workflow is ideal for: Domain investors and flippers who need to check multiple domains quickly Web developers and agencies evaluating domain options for client projects Digital marketers researching domain availability for campaigns Business owners exploring domain options for new ventures IT professionals managing domain portfolios Users should have basic familiarity with n8n workflow concepts and a Namesilo account to obtain an API key. No coding knowledge is required, though understanding of domain name systems would be beneficial. What problem is this workflow solving? Checking domain availability one-by-one is a time-consuming and tedious process, especially when dealing with dozens or hundreds of potential domains. This workflow solves several key challenges: Manual Inefficiency: Eliminates the need to individually search for each domain through registrar websites. Rate Limiting: Handles API rate limits automatically with built-in waiting periods. Data Organization: Compiles availability results into a structured Excel file rather than scattered notes or multiple browser tabs. Bulk Processing: Processes up to 200 domains per batch, with the ability to handle unlimited domains across multiple batches. Time Management: Frees up valuable time that would otherwise be spent on repetitive manual checks. What this workflow does Overview The workflow takes a list of domains, processes them in batches of up to 200 domains per request (to comply with API limitations), checks their availability using the Namesilo API, and compiles the results into an Excel spreadsheet showing which domains are available for registration and which are already taken. Process Input Setup: The workflow begins with a manual trigger and uses the "Set Data" node to collect the list of domains to check and your Namesilo API key. Domain Processing: The "Convert & Split Domains" node transforms the input list into batches of up to 200 domains to comply with API limitations. Batch Processing: The workflow loops through each batch of domains. API Integration: For each batch, the "Namesilo Requests" node sends a request to the Namesilo API to check domain availability. Data Parsing: The "Parse Data" node processes the API response, extracting information about which domains are available and which are taken. Rate Limit Management: A 5-minute wait period is enforced between batches to respect Namesilo's API rate limits. Data Compilation: The "Merge Results" node combines all the availability data. Output Generation: Finally, the "Convert to Excel" node creates an Excel file with two columns: Domain and Availability (showing "Available" or "Unavailable" for each domain). Setup Import the workflow: Download the workflow JSON file and import it into your n8n instance. Get Namesilo API key: Create a free account at Namesilo and obtain your API key from https://www.namesilo.com/account/api-manager Configure the workflow: Open the "Set Data" node Enter your Namesilo API key in the "Namesilo API Key" field Enter your list of domains (one per line) in the "Domains" field Save and activate: Save the workflow and run it using the manual trigger. How to customize this workflow to your needs Modify domain input format: You can adjust the code in the "Convert & Split Domains" node if your domain list comes in a different format. Change batch size: If needed, you can modify the batch size (currently set to 200) in the "Convert & Split Domains" node to accommodate different API limitations. Adjust wait time: If you have a premium API account with different rate limits, you can modify the wait time in the "Wait" node. Enhance output format: Customize the "Convert to Excel" node to add additional columns or formatting to the output file. Add domain filtering: You could add a node before the API request to filter domains based on specific criteria (length, keywords, TLDs). Integrate with other services: Connect this workflow to domain registrars to automatically register available domains that meet your criteria.
By n8n custom workflowsAI-powered news monitoring & social post generator with OpenAI and Upload-Post
This automation template turns any RSS feed into ready-to-publish social content using AI. It continuously ingests articles, scores their quality and relevance, crafts platform-native posts (Twitter/X threads and LinkedIn posts), routes items for review or archiving, logs everything to Google Sheets, and can publish automatically to X, Threads, and LinkedIn. Note: This workflow uses OpenAI models for analysis and content generation and integrates with Upload-Post for multi-platform publishing and Google Sheets for tracking. Costs depend on token usage and posting volume. Who Is This For? Content Teams & Solo Creators: Ship consistent, high-signal posts without manual rewriting. Newsletters & Media Brands: Turn breaking stories into shareable, platform-native content. Agencies: Scale curation across clients with review and auto-publish paths. Founders & PMMs: Maintain a steady public presence with minimal effort. What Problem Does This Workflow Solve? Manual curation and rewriting of news is slow and inconsistent. This workflow: Scores Articles: Filters noise with AI quality/relevance scoring. Auto-Writes Posts: Generates concise X threads and business-ready LinkedIn copy. Routes Intelligently: Sends good items to publish/review and archives the rest. Logs Everything: Keeps a structured history in Google Sheets for analytics. How It Works RSS Polling: Monitors your chosen feed(s) on a schedule. Scoring AI: Rates quality and relevance; extracts summary, key topics, and angle. Parse & Enrich: Normalizes AI output and merges with article metadata. Quality Gates: Directs items to “publish/review” or “archive.” Content Generation: Produces an X thread and a LinkedIn post with clear hooks and insights. Publishing: Uploads to X, Threads, and LinkedIn via Upload-Post (optional). Sheets Logging: Writes summaries, scores, and outputs to Google Sheets. Setup OpenAI API: Add your OpenAI credentials (models like gpt-4.1/gpt-4o). Upload-Post Credentials: Connect the Upload-Post integration and target pages (e.g., LinkedIn org ID). Google Sheets: Add OAuth credentials and point “Store Content”/“New for Review”/“Archive” to your sheets. RSS Feed URL: Replace the sample feed with your preferred sources. Thresholds & Routing: Adjust quality/relevance filters to your standards. Publishing Mode: Toggle platforms (X, Threads, LinkedIn) and decide auto vs. review-first. Requirements Accounts: n8n, OpenAI, Upload-Post, Google account (Sheets). API Keys: OpenAI token, Upload-Post credentials, Google Sheets OAuth. Feeds: One or more RSS URLs for your niche. Features AI Triage: Quality/relevance scoring to prioritize high-value stories. Platform-Native Output: Hooked X threads and professional LinkedIn posts. Review or Auto-Publish: Safe gating before posting live. Analytics-Ready Logs: Structured entries in Google Sheets. Modular & Extensible: Swap feeds, add Slack/Discord alerts, or plug into CMS/Notion. Stay top-of-mind: convert fresh news into compelling, on-brand social content—automatically.
By Juan Carlos Cavero GraciaGenerate Facebook marketing content from images with Telegram & Gemini
📝 Description Instantly turn images into marketing content with one Telegram message. It automatically: Accepts an image and caption via Telegram Sends the image to an AI model with your brand’s content rules Generates copy with headline, body, hashtags, and CTA Sends it back to you for approval On approval, posts directly to your Facebook Page If rejected or sent as plain text, request edits and it will regenerate your content 🎯 Key Advantages for Content Teams ✅ Creates professional post content from raw images in seconds ✅ Keeps the process inside Telegram—no app-switching ✅ Allows fast edits through natural text replies ✅ Reduces creative workload using your own AI style guide ✅ Posts directly to Facebook—no copy-pasting needed 🛠️ Features Telegram Bot Trigger (via Telegram API) Image file parsing + downloading AI Content Generation using OpenRouter + LangChain Custom Brand Prompt: Hook + Content + CTA in natural Arabic JSON Parsing with fallback handling Dual approval route (human- or bot-origin) Facebook publishing via Graph API Retry loop: users can request changes directly Sticky notes on all nodes for fast onboarding 🔧 Requirements Telegram Bot Token Facebook Page access with pagesmanageposts + pagesreadengagement OpenRouter API key (or another LLM provider) n8n credentials for: Telegram Bot Facebook (OAuth or Bearer token) OpenRouter (or alternative) 🧠 Use Case Examples 🧴 Beauty Brands: Auto-generate Arabic content from new skincare routine photos 🏥 Clinics: Transform testimonial photos into compliant social posts 🧢 Streetwear Shops: Quickly convert customer-submitted photos into engaging product drops 📚 Education Pages: Teachers send photos and instantly get shareable awareness content 🐾 Pet Pages: Easily publish heartfelt stories from community-submitted photos ⚙️ Customization Tips Edit the Brand Prompt Update the AI node with your own brand tone, examples, and structure. Switch LLMs Swap the OpenRouter model with Gemini, GPT-4, or others by changing the LLM node. Change Post Target Replace the Facebook post URL with Instagram or your CMS webhook. Customize Loop Logic Adjust the re-triggering workflow to better match your desired Telegram conversation UX. If you need any help Get in touch
By Abdullah AlshiekhYouTube video optimization & cross-platform distribution with GPT-4o
This workflow automates the post-publish process for YouTube videos, combining advanced SEO optimization, cross-platform promotion, and analytics reporting. It is designed for creators, marketers, and agencies who want to maximize the reach and performance of their YouTube content with minimal manual effort. --- Features SEO Automation Fetches video metadata and analyzes competitor and trending data. Uses AI to generate SEO-optimized titles, descriptions, and tags. Calculates an SEO score and applies A/B testing logic to select the best title. Updates the video metadata on YouTube automatically. Cross-Platform Promotion Generates platform-specific promotional content (LinkedIn, X/Twitter, Instagram, Facebook, etc.) using AI. Publishes posts to each connected social channel. Extracts video clips and analyzes thumbnails for enhanced promotion. Engagement Monitoring & Analytics Monitors YouTube comments, detects negative sentiment, and drafts AI-powered replies. Logs all key data (videos, comments, analytics) to Google Sheets for tracking and reporting. Runs a weekly analytics job to aggregate performance, calculate engagement/viral indicators, and email a detailed report. Notifications & Alerts Sends Slack alerts when a new video is published or when viral potential/negative comments are detected. --- How It Works Trigger The workflow starts automatically when a new YouTube video is published (via webhook) or on a weekly schedule for analytics. Video Intake & SEO Fetches video details (title, description, tags, stats). Gathers competitor and trending topic data. Uses AI to generate improved SEO assets and calculates an SEO score. Selects the best title (A/B test) and updates the video metadata. Clip & Thumbnail Processing If the video is long enough, runs thumbnail analysis and extracts short clips for social media. Cross-Platform Promotion Generates and formats promotional posts for each social platform. Publishes automatically to enabled channels. Engagement & Comment Monitoring Fetches comments, detects negative sentiment, and drafts AI-powered replies. Logs comments and responses to Google Sheets. Analytics & Reporting Aggregates weekly analytics, calculates engagement and viral indicators. Logs insights and sends a weekly report via email. Notifications Sends Slack alerts for new video publications and viral/negative comment detection. --- Setup Instructions Connect YouTube Set up YouTube API credentials and required IDs in the Workflow Configuration node. Connect OpenAI Add your OpenAI credentials for AI-powered content generation. Connect Slack Configure Slack credentials and specify alert channels. Connect Google Sheets Set up service account credentials for logging video, comment, and analytics data. Configure Social Platforms Add credentials for LinkedIn, Twitter (X), Instagram, and Facebook as needed. Test the Workflow Publish a test video and verify that metadata updates, social posts, logging, and weekly reports are working as expected. --- Use Cases YouTube Creators: Automate SEO, promotion, and analytics to grow your channel faster. Marketing Teams: Streamline multi-channel video campaigns and reporting. Agencies: Deliver consistent, data-driven YouTube growth for multiple clients. --- Requirements YouTube API credentials OpenAI API key Slack API token Google Sheets service account (Optional) LinkedIn, Twitter, Instagram, Facebook API credentials --- Limitations Requires valid API credentials for all connected services. AI-powered features depend on OpenAI API access. Social posting is limited to platforms with available n8n nodes and valid credentials. --- Tip: You can easily customize prompts, scoring logic, and enabled platforms to fit your channel’s unique needs.
By Țugui DragoșAI-powered Gmail assistant: send replies by analyzing thread ID with Sonnet 4.5
This workflow automates analyzing Gmail threads and drafting AI-powered replies with the new model Anthropic Sonnet 4.5. This workflow automates the process of analyzing incoming emails and generating context-aware draft replies by examining the entire email thread. --- Key Advantages ✅ Time-Saving – Automates repetitive email replies, reducing manual workload. ✅ Context-Aware Responses – Replies are generated using the entire email thread, not just the latest message. ✅ Smart Filtering – The classifier prevents unnecessary drafts for spam or promotional emails. ✅ Human-in-the-Loop – Drafts are created instead of being sent immediately, allowing manual review and corrections. ✅ Scalable & Flexible – Can be adapted to different accounts, reply styles, or workflows. ✅ Seamless Gmail Integration – Directly interacts with Gmail threads and drafts via OAuth. --- How it Works This workflow automates the process of analyzing incoming emails and generating context-aware draft replies by examining the entire email thread. Trigger & Initial Filtering: The workflow is automatically triggered every minute by the Gmail Trigger node, which detects new emails. For each new email, it immediately performs a crucial first step: it uses an AI Email Classifier to analyze the email snippet. The AI determines if the email is a legitimate message that warrants a reply (categorized as "ok") or if it's spam, a newsletter, or an advertisement. This prevents the system from generating replies for unwanted emails. Context Aggregation: If an email is classified as "ok," the workflow fetches the entire conversation thread from Gmail using the threadId. A Code Node then processes all the messages in the thread, structuring them into a consistent format that the AI can easily understand. AI-Powered Draft Generation: The structured conversation history is passed to the Replying email Agent with Sonnet 4.5. This agent, powered by a language model, analyzes the entire thread to understand the context and the latest inquiry. It then drafts a relevant and coherent HTML email reply. The system prompt instructs the AI not to invent information and to use placeholders for any missing details. Draft Creation: The final step takes the AI-generated reply and the original email's metadata (subject, recipient, threadId) and uses them to create a new draft email in Gmail. This draft is automatically placed in the correct email thread, ready for the user to review and send. --- Set up Steps To implement this automated email reply system, you need to configure the following: Configure Gmail & OpenAI Credentials: Ensure the following credentials are set up in your n8n instance: Gmail OAuth2 Credentials: The workflow uses the same Gmail account for the trigger, fetching threads, and creating drafts. Configure this in the "Gmail Trigger," "Get a thread," and "Create a draft" nodes. OpenAI API Credentials: Required for both the "Email Classifier". Provide your API key in the respective OpenAI Chat Model nodes. Anthropic API Credentials: Required for the main "Replying email Agent." Provide your API key in the respective Antrhopic Chat Model nodes. Review AI Classification & Prompting: Email Filtering: Check the categories in the Email Classifier node. The current setup marks only non-advertising, non-newsletter emails as "ok." You can modify these categories to fit your specific needs and reduce false positives. Reply Agent Instructions: Review the system message in the Replying email Agent. You can customize the AI's persona, tone, and instructions (e.g., making it more formal, or instructing it to sign with a specific name) to better align with your communication style. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By DavideGenerate daily Jira summaries & weekly reports with Azure OpenAI and Gmail
Description Automates daily EOD summaries from Jira issues into an Excel sheet, then compiles a weekly summary using Azure OpenAI (GPT-4o-mini) and delivers it to stakeholders via email. Gain consistent reporting, clear insights, and hands-free delivery. ✨📧 What This Template Does Fetches Jira issues and extracts key fields. 🧩 Generates End‑of‑Day summaries and stores them in Excel daily. 📄 Aggregates the week’s EOD data from Excel. 📚 Creates a weekly summary using Azure OpenAI (GPT-4o-mini). 🤖 Delivers the weekly report to stakeholders via email. 📬 Key Benefits Saves time with fully automated daily and weekly reporting. ⏱️ Ensures consistent, structured summaries every time. 📏 Improves clarity for stakeholders with readable insights. 🪄 Produces mobile-friendly email summaries for quick consumption. 📱 No-code customization inside n8n. 🛠 Features Jira issue ingestion and transformation. Daily EOD summary generation and Excel storage. Weekly AI summarization with Azure OpenAI (GPT-4o-mini). Styled HTML email output to stakeholders. Scheduling for hands-free execution. Requirements An n8n instance (cloud or self-hosted). Jira access to read issues. Azure OpenAI (GPT-4o-mini) for weekly AI summarization. Email service (Gmail/SMTP) configured in n8n credentials. Excel/Sheet storage set up to append and read daily EOD entries. Target Audience Engineering and product teams needing routine summaries. Project managers tracking daily progress. Operations teams consolidating weekly reporting. Stakeholders who prefer clean email digests. Step-by-Step Setup Instructions Jira: Connect your Jira credentials and confirm issue read access. Azure OpenAI: Deploy GPT-4o-mini and add Azure OpenAI credentials in n8n. Gmail/SMTP: Connect your email account in n8n Credentials and authorize sending. Excel/Sheet: Configure the sheet used to store daily EOD summaries. Import the workflow, assign credentials to nodes, replace placeholders, then run and schedule. Security Best Practices Use scoped API tokens for Jira with read-only permissions. 🔐 Store Azure OpenAI and email credentials in n8n’s encrypted credentials manager. 🧯 Limit email recipients to approved stakeholder lists. 🚦 Review logs regularly and rotate credentials on a schedule. ♻
By Rahul JoshiPlant care reminder with OpenWeather, Sheets and Telegram
This workflow automates plant care reminders and records using Google Sheets, Telegram, and OpenWeather API. It checks when each plant needs watering or fertilizing, sends a personalized reminder, and lets you confirm the task with a single button. When confirmed, it updates your Google Sheet and shows a confirmation HTML page. Who is it for? Home gardeners who want to automate watering and fertilizing schedules. Anyone managing a plant collection, greenhouse, or garden and wanting a lightweight, no-code reminder system. How it works Schedule Trigger starts the workflow once per day. Read Settings (Google Sheets) checks if vacation_mode is active. Read Plants (Google Sheets) retrieves all plants with columns such as id, plant, lastwater, waterfreq, etc. DecideDue (Code Node) compares today’s date with the last watering/fertilizing date and marks which plants are due. OpenWeather Request (optional) fetches local forecast for plants with coordinates and weather_delay = true. WeatherGate (Code Node) skips or delays watering if it recently rained or if rain is expected soon. Telegram Send Message sends a reminder for each due task. The message contains an inline button “Mark as done” linking to your webhook URL (opens confirmation window). Webhook – Confirm Done receives the click, update dates on Google Sheets, appends an optional log entry, and returns an HTML confirmation page. Setup steps Principal Workflow Spreadsheet- Create a Google Sheets document with: plants sheet: (id, plant, lastwater, waterfreq, lastfert, fertfreq, lat, lon, weatherdelay , indoor, thirstlevel) settings sheet: (vacation_mode, timezone) log sheet: (ts, plantid, action messageid) Connect your Google account Configure the Schedule Trigger Enable weather integration (Get a free OpenWeather API key) and add it to the HTTP Request node parameters appid. https://openweathermap.org/api Configure Telegram with your credential and your chat id on {YOURCHATID}. Configure "Send Dues" node with your custom url https://{YOURPROJECTURL}.app.n8n... Setup steps Sub-Workflow (Webhook) Trigger: Configure your custom Path. Google Sheets: Connect your Google Account and Map sheets and columns. Requirements · A Google account with access to Google Sheets. . A spreadsheet containing three sheets with headers matching the field names used in the workflow. . A telegram bot. . OpenWeather API key for climate-aware watering. How to customise it Add plant photos: Include a photo URL column and show it in the Telegram message. Extend actions: Add pruning, repotting or any other periodic task by duplicating the existing logic.
By Adrian🛠️ CircleCI tool MCP server
🛠️ 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 David AshbyBuild a website-powered customer support chatbot with Decodo, Pinecone and Gemini
Categories: Business Automation, Customer Support, AI, Knowledge Management This comprehensive workflow enables businesses to build and deploy a custom-trained AI Chatbot in minutes. By combining a sophisticated data scraping engine with a RAG-based (Retrieval-Augmented Generation) chat interface, it allows you to transform website content into a high-performance support agent. Powered by Google Gemini and Pinecone, this system ensures your chatbot provides accurate, real-time answers based exclusively on your business data. Benefits Instant Knowledge Sync - Automatically crawls sitemaps and URLs to keep your AI up-to-date with your latest website content. Embeddable Anywhere - Features a ready-to-use chat trigger that can be integrated into the bottom-right of any website via a simple script. High-Fidelity Retrieval - Uses vector embeddings to ensure the AI "searches" your documentation before answering, reducing hallucinations. Smart Conversational Memory - Equipped with a 10-message window buffer, allowing the bot to handle complex follow-up questions naturally. Cost-Efficient Scaling - Leverages Gemini’s efficient API and Pinecone’s high-speed indexing to manage thousands of customer queries at a low cost. How It Works Dual-Path Ingestion: The process begins with an n8n Form where you provide a sitemap or individual URLs. The workflow automatically handles XML parsing and URL cleaning to prepare a list of pages for processing. Clean Content Extraction: Using Decodo, the workflow fetches the HTML of each page and uses a specialized extraction node to strip away code, ads, and navigation, leaving only the high-value text content. SignUp using: dashboard.decodo.com/register?referral_code=55543bbdb96ffd8cf45c2605147641ee017e7900. Vectorization & Storage: The cleaned text is passed to the Gemini Embedding model, which converts the information into 3076-dimensional vectors. These are stored in a Pinecone "supportbot" index for instant retrieval. RAG-Powered Chat Agent: When a user sends a message through the chat widget, an AI Agent takes over. It uses the user's query to search the Pinecone database for relevant business facts. Intelligent Response Generation: The AI Agent passes the retrieved facts and the current chat history to Google Gemini, which generates a polite, accurate, and contextually relevant response for the user. Requirements n8n Instance: A self-hosted or cloud instance of n8n. Google Gemini API Key: For text embeddings and chat generation. Pinecone Account: An API key and a "supportbot" index to store your knowledge base. Decodo Access: For high-quality website content extraction. How to Use Initialize the Knowledge Base: Use the Form Trigger to input your website URL or Sitemap. Run the ingestion flow to populate your Pinecone index. Configure Credentials: Authenticate your Google Gemini and Pinecone accounts within n8n. Deploy the Chatbot: Enable the Chat Trigger node. Use the provided webhook URL to connect the backend to your website's frontend chat widget. Test & Refine: Interact with the bot to ensure it retrieves the correct data, and update your knowledge base by re-running the ingestion flow whenever your website content changes. Business Use Cases Customer Support Teams - Automate answers to 80% of common FAQs using your existing documentation. E-commerce Sites - Help customers find product details, shipping policies, and return information instantly. SaaS Providers - Build an interactive technical documentation assistant to help users navigate your software. Marketing Agencies - Offer "AI-powered site search" as an add-on service for client websites. Efficiency Gains Reduce Ticket Volume by providing instant self-service options. Eliminate Manual Data Entry by scraping content directly from the live website. Improve UX with 24/7 availability and zero wait times for customers. Difficulty Level: Intermediate Estimated Setup Time: 30 min Monthly Operating Cost: Low (variable based on AI usage and Pinecone tier)
By Zain Khan