HumationHuman + Automation
Back to Catalog

YouTube analytics data reporting API integration for AI agents

David AshbyDavid Ashby
149 views
2/3/2026
CloudMQTTAWSS3Integration
Official Page

Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

Join the community

Complete MCP server exposing 8 YouTube Reporting API operations to AI agents.

⚡ Quick Setup

  1. Import this workflow into your n8n instance
  2. Credentials Add YouTube Reporting API credentials
  3. Activate the workflow to start your MCP server
  4. Copy the webhook URL from the MCP trigger node
  5. Connect AI agents using the MCP URL

🔧 How it Works

This workflow converts the YouTube Reporting 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://youtubereporting.googleapis.com/ • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent

📋 Available Operations (8 total)

🔧 V1 (8 endpoints)

• GET /v1/jobs: Retrieve Report Metadata • POST /v1/jobs: Creates a job and returns it. • DELETE /v1/jobs/{jobId}: Deletes a job. • GET /v1/jobs/{jobId}: Gets a job. • GET /v1/jobs/{jobId}/reports: Lists reports created by a specific job. Returns NOT_FOUND if the job does no... • GET /v1/jobs/{jobId}/reports/{reportId}: Gets the metadata of a specific report. • GET /v1/media/{resourceName}: Method for media download. Download is supported on the URI `/v1/media/{+name... • GET /v1/reportTypes: List Report Types

🤖 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 YouTube Reporting 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.

n8n YouTube Analytics Data Reporting API Integration for AI Agents

This n8n workflow serves as a foundational Model Context Protocol (MCP) server, designed to be integrated with AI agents. It acts as a trigger point, signaling to an AI agent that a specific context or task related to YouTube analytics data reporting is ready to be processed or initiated.

What it does

This workflow provides a basic MCP server trigger, allowing AI agents to initiate processes or retrieve information.

  1. Listens for MCP Requests: The workflow starts with an "MCP Server Trigger" node, which listens for incoming requests from AI agents adhering to the Model Context Protocol.
  2. Provides a Contextual Starting Point: When triggered, it provides a defined entry point for AI agents to interact with, enabling them to initiate subsequent actions related to YouTube analytics data.
  3. Includes a Sticky Note for Documentation: A "Sticky Note" is included for internal documentation or notes regarding the workflow's purpose or specific instructions.

Prerequisites/Requirements

  • n8n Instance: An active n8n instance where this workflow can be imported and run.
  • AI Agent: An AI agent capable of sending requests to an MCP server and interpreting its responses.
  • Understanding of Model Context Protocol (MCP): Familiarity with how MCP works for integrating AI agents with n8n workflows.

Setup/Usage

  1. Import the workflow: Import the provided JSON into your n8n instance.
  2. Configure the MCP Server Trigger: The "MCP Server Trigger" node is pre-configured to listen for incoming MCP requests. No additional configuration is typically needed unless you want to change the listening port or other advanced settings (usually handled at the n8n instance level).
  3. Integrate with your AI Agent: Configure your AI agent to send requests to the URL exposed by this "MCP Server Trigger" node. The specific URL will be displayed in the n8n editor once the workflow is active.
  4. Expand the workflow: This workflow is a starting point. You would typically add subsequent nodes after the "MCP Server Trigger" to:
    • Connect to the YouTube Analytics Data Reporting API.
    • Fetch specific analytics data based on parameters provided by the AI agent.
    • Process and format the data.
    • Send the processed data back to the AI agent or another destination (e.g., a database, a reporting tool, a messaging service).

Related Templates

Automate event RSVPs with email validation & badge generation using VerifiEmail & HTMLCssToImage

Validated RSVP Confirmation with Automated Badge Generation Overview: This comprehensive workflow automates the entire event RSVP process from form submission to attendee confirmation, including real-time email validation and personalized digital badge generation. ✨ KEY FEATURES: • Real-time Email Validation - Verify attendee emails using VerifiEmail API to prevent fake registrations • Automated Badge Generation - Create beautiful, personalized event badges with attendee details • Smart Email Routing - Send confirmation emails with badges for valid emails, rejection notices for invalid ones • Comprehensive Logging - Track all RSVPs (both valid and invalid) in Google Sheets for analytics • Dual Path Logic - Handle valid and invalid submissions differently with conditional branching • Anti-Fraud Protection - Detect disposable emails and invalid domains automatically 🔧 WORKFLOW COMPONENTS: Webhook Trigger - Receives RSVP submissions Email Validation - Verifies email authenticity using VerifiEmail API Conditional Logic - Separates valid from invalid submissions Badge Creator - Generates HTML-based personalized event badges Image Converter - Converts HTML badges to shareable PNG images using HTMLCssToImage Email Sender - Delivers confirmation with badge or rejection notice via Gmail Data Logger - Records all attempts in Google Sheets for tracking and analytics 🎯 PERFECT FOR: • Conference organizers managing hundreds of RSVPs • Corporate event planners requiring verified attendee lists • Webinar hosts preventing fake registrations • Workshop coordinators issuing digital badges • Community event managers tracking attendance 💡 BENEFITS: • Reduces manual verification time by 95% • Eliminates fake email registrations • Creates professional branded badges automatically • Provides real-time RSVP tracking and analytics • Improves attendee experience with instant confirmations • Maintains clean, verified contact lists 🛠️ REQUIRED SERVICES: • n8n (cloud or self-hosted) • VerifiEmail API (https://verifi.email) • HTMLCssToImage API (https://htmlcsstoimg.com) • Gmail account (OAuth2) • Google Sheets 📈 USE CASE SCENARIO: When someone submits your event RSVP form, this workflow instantly validates their email, generates a personalized badge with their details, and emails them a confirmation—all within seconds. Invalid emails receive a helpful rejection notice, and every submission is logged for your records. No manual work required! 🎨 BADGE CUSTOMIZATION: The workflow includes a fully customizable HTML badge template featuring: • Gradient background with modern design • Attendee name, designation, and organization • Event name and date • Email address and validation timestamp • Google Fonts (Poppins) for professional typography 📊 ANALYTICS INCLUDED: Track metrics like: • Total RSVPs received • Valid vs invalid email ratio • Event-wise registration breakdown • Temporal patterns • Organization/company distribution ⚡ PERFORMANCE: • Processing time: ~3-5 seconds per RSVP • Scales to handle 100+ concurrent submissions • Email delivery within 10 seconds • Real-time Google Sheets updates 🔄 EASY SETUP: Import the workflow JSON Configure your credentials (detailed instructions included) Create your form with required fields (name, email, event, designation, organization) Connect the webhook Activate and start receiving validated RSVPs! 🎓 LEARNING VALUE: This workflow demonstrates: • Webhook integration patterns • API authentication methods • Conditional workflow branching • HTML-to-image conversion • Email automation best practices • Data logging strategies • Error handling techniques ---

Jitesh DugarBy Jitesh Dugar
67

Generate Funny AI Videos with Sora 2 and Auto-Publish to TikTok

This automation creates a fully integrated pipeline to generate AI-powered videos, store them, and publish them on TikTok — all automatically. It connects OpenAI Sora 2, and Postiz (for TikTok publishing) to streamline content creation. --- Key Benefits ✅ Full Automation – From text prompt to TikTok upload, everything happens automatically with no manual intervention once set up. ✅ Centralized Control – Google Sheets acts as a simple dashboard to manage prompts, durations, and generated results. ✅ AI-Powered Creativity – Uses OpenAI Sora 2 for realistic video generation and GPT-5 for optimized titles. ✅ Social Media Integration – Seamlessly posts videos to TikTok via Postiz, ready for your audience. ✅ Scalable & Customizable – Can easily be extended to other platforms like YouTube, Instagram, or LinkedIn. ✅ Time-Saving – Eliminates repetitive steps like manual video uploads or caption writing. --- How it works This workflow automates the end-to-end process of generating AI videos and publishing them to TikTok. It is triggered either manually or on a recurring schedule. Trigger & Data Fetch: The workflow starts by checking a specified Form for new entries. It looks for rows where a video has been requested (a "PROMPT" is filled) but not yet generated (the "VIDEO" column is empty). AI Video Generation: For each new prompt found, the workflow sends a request to the Fal.ai Sora 2 model to generate a video. It then enters a polling loop, repeatedly checking the status of the generation request every 60 seconds until the video is "COMPLETED". Post-Processing & Upload: Once the video is ready, the workflow performs several actions in parallel: Fetch Video & Store: It retrieves the final video URL, downloads the video file Generate Title: It uses the OpenAI GPT-4o-mini model to analyze the original prompt and generate an optimized, engaging title for the video. Publish to TikTok: The video file is uploaded to Postiz, a social media scheduling tool, which then automatically publishes it to a connected TikTok channel, using the AI-generated title as the post's caption. --- Set up steps To make this workflow functional, you need to complete the following configuration steps: Prepare the Google Sheet: Create a Form with at least "PROMPT", "DURATION", and "VIDEO" fields. Configure Fal.ai for Video Generation: Create an account at Fal.ai and obtain your API key. In both the "Create Video" and "Get status" HTTP Request nodes, set up the "Header Auth" credential. Set the Name to Authorization and the Value to Key YOURAPIKEY. Set up TikTok Publishing via Postiz: Create an account on Postiz and connect your TikTok account to get a Channel ID. Obtain your Postiz API key. In the "Upload Video to Postiz" and "TikTok" (Postiz) nodes, configure the API credentials. In the "TikTok" node, replace the placeholder "XXX" in the integrationId field with your actual TikTok Channel ID from Postiz. (Optional) Configure AI Title Generation: The "Generate title" node uses OpenAI. Ensure you have valid OpenAI API credentials configured in n8n for this node to work. --- Need help customizing? Contact me for consulting and support or add me on Linkedin. Header 2

DavideBy Davide
24772

Automate bank statement and invoice reconciliation with GPT and Google Sheets

🟢 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.

Chintan PrajapatiBy Chintan Prajapati
447