OpenClaw + n8n Webhook Tutorial: Collect YouTube Metadata with an AI Agent

OpenClaw + n8n Webhook Tutorial: Collect YouTube Metadata with an AI Agent

L
LBSocial
May 7, 2026  #OpenClaw #n8n #AIAgents

In this week's tutorial, we demonstrate how to connect your OpenClaw AI agent to an n8n automation workflow using a Webhook. Learn how to securely extract YouTube video metadata without ever exposing your API keys to the LLM!

By decoupling the reasoning engine (OpenClaw via Telegram) from the execution engine (n8n on a Google Cloud VM), we create a highly secure, scalable, and mobile-friendly automation pipeline. You can trigger complex automations right from your phone while keeping all the logic and credentials safely stored in n8n.

📚 Full OpenClaw Tutorial Series:
Catch up on our complete guide to building and deploying AI agents:
👉 https://www.youtube.com/playlist?list=PLHutrxqbP1BwAQf6dROCLZqK0PLpGu35J

🌐 Code Snippets & Blog Post:
Get all the JavaScript code nodes, prompts, and detailed implementation notes on our LBSocial blog (The full post for this episode will be updated very soon!):
👉 https://www.lbsocial.net/post/n8n-webhook-openclaw-youtube-api-tutorial

⏱️ Timeline & Chapters:
00:00 - Demo: Triggering n8n from Telegram via OpenClaw
00:43 - Architecture overview: OpenClaw + n8n + Webhook
01:29 - Setting up the YouTube Data API v3 Key in Google Cloud
02:40 - Storing API Credentials securely in n8n
03:16 - Building the n8n workflow: Extracting Video ID
04:41 - HTTP Request Node: Fetching YouTube Metadata
06:05 - Data Cleaning: Using JavaScript to extract topics & stats
07:08 - Understanding Webhooks: How OpenClaw talks to n8n
07:53 - Setting up the Webhook Trigger Node (POST Request)
09:01 - Adding the "Respond to Webhook" Node for synchronous replies
10:07 - Creating an OpenClaw Skill using the Skill Creator
11:49 - Testing the complete AI Agent automation flow
12:19 - Architecture Summary: Why decouple AI from execution?

💡 Key Takeaways:

Security: Keep API keys in n8n credentials, not in your agent's scripts.

Efficiency: Use n8n to clean massive JSON payloads so your LLM uses fewer tokens.

Flexibility: Trigger complex automations from anywhere using Telegram.

If you found this helpful, don't forget to Like, Comment, and Subscribe for more tutorials on learning Data Science in the cloud with AI!

#OpenClaw #n8n #AIAgents #Webhooks #YouTubeAPI #Automation #DataScience #CloudComputing #LBSocial

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