This article provides a complete, practical walkthrough of the Http Executeworkflow Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   **Title:**  
   How to Build an AI-Powered YouTube Content Assistant Using n8n & OpenAI
   
   **Meta Description:**  
   Learn how to create an AI agent with n8n to automatically analyze YouTube videos, extract user insights from comments, transcribe video content, and evaluate thumbnails using OpenAI, Apify, and Google APIs.
   
   **Keywords:**  
   n8n workflow, YouTube AI assistant, OpenAI n8n integration, video comment analysis, YouTube video transcription, thumbnail analysis, Apify YouTube automation, YouTube API tutorial, content optimization with AI, YouTube channel insights
   
   ---
   
   ## Build an AI-Powered YouTube Content Assistant with n8n
   
   In the fast-paced world of content creation, understanding your audience and refining content strategy is crucial. Manual analysis of videos, comments, and engagement data is time-consuming. But what if an AI agent could automate it all?
   
   Thanks to n8n, an open-source workflow automation tool, creators can now build an intelligent YouTube Assistant. This no-code/low-code automation uses AI models and data extraction APIs to analyze YouTube content, comments, thumbnails, and video transcripts—helping you create more engaging and data-driven videos.
   
   ### What the Workflow Does
   
   Created by Mark Shcherbakov from the [5minAI](https://www.skool.com/5minai) community, the workflow integrates multiple APIs with OpenAI and a memory database to deliver a fully automated YouTube analysis pipeline. It’s designed specifically for content creators, marketers, and researchers who want fast insights without diving into code.
   
   Here's what the AI-powered agent can do:
   - Identify popular YouTube creators and retrieve their content.
   - Analyze comments for audience preferences and feedback.
   - Transcribe full video content for clarity and repurposing.
   - Evaluate video thumbnails using OpenAI’s image analysis.
   - Organize and store data efficiently for future research or planning.
   
   Let’s take a closer look at how this all works.
   
   ---
   
   ### Key Features of the AI YouTube Assistant Workflow
   
   #### 1. Automated YouTube Channel & Video Retrieval  
   Using the YouTube Data API, the workflow fetches channel and video details by either username or video ID. This includes:
   - Channel ID, title, and description.
   - Video title, full description, duration, likes, and views.
   - A list of videos by channel, sorted by date, relevance, or popularity.
   
   This data is powered by tools such as:
   - `get_channel_details`
   - `get_list_of_videos`
   - `get_video_description`
   
   #### 2. Comment Analysis with AI  
   By collecting viewer comments through the YouTube API, the agent processes sentiment, identifies frequently discussed topics, and summarizes feedback. This enables content creators to fine-tune their messaging based on concrete audience data.
   
   To handle pagination and pull full comment threads, the workflow applies logic within the `get_list_of_comments` tool, then formats output via custom Set nodes.
   
   #### 3. Advanced Video Transcription with Apify  
   The agent uses Apify’s actor to transcribe video content. This is invaluable for:
   - Creating subtitles or captions.
   - Summarizing video themes.
   - Repurposing content into blog posts or scripts.
   
   Each transcript is extracted with the `video_transcription` tool and can be analyzed or stored for content planning.
   
   #### 4. Thumbnail Analysis Using OpenAI Vision  
   An innovative feature of the workflow is AI-based thumbnail evaluation. With OpenAI’s GPT-4 Vision model, the assistant can critique thumbnails for visual composition, readability, and appeal. You simply provide the `maxRes` image URL and a prompt (e.g., “How eye-catching is this design?”), and it returns analytical insight.
   
   This is enabled via the `analyze_thumbnail` tool and OpenAI’s image analysis API.
   
   #### 5. AI-Powered Chat Interface with Context Memory  
   The centerpiece of the workflow is an AI agent that understands natural language questions and executes the backend tools in the correct sequence. It acts as a YouTube virtual assistant powered by:
   - GPT-4 via the `OpenAI Chat Model`
   - `Postgres Chat Memory` to preserve session history
   - Routing logic for dynamically executing the correct tools (`video_details`, `search`, etc.)
   
   An example query might be:
   > "Find the last 5 videos from @example_channel and tell me what viewers liked most about them."
   
   The agent structures the task, gets the channel ID, fetches video details, pulls comments, and synthesizes user insights—all in minutes.
   
   ---
   
   ### How to Set It Up
   
   To get started, the workflow requires:
   1. **APIs & Credentials**
      - Google Cloud project (for YouTube Data API).
      - Apify account and API key.
      - OpenAI account with GPT-4 access.
      - Credentials stored securely in n8n.
   
   2. **Workflow Deployment**
      - Import the predefined n8n workflow.
      - Replace credentials where needed.
      - Optionally watch the step-by-step setup video (13 min): [Setup Tutorial on YouTube](https://youtu.be/6RmLZS8Yl4E)
   
   3. **Custom Queries**
      - Use the chat input to interact with the assistant.
      - Or program static queries in n8n’s UI for scheduled reports.
   
   ---
   
   ### Third-Party APIs Used
   
   Here is a complete list of third-party services integrated into the workflow:
   
   | API/Service        | Purpose |
   |---------------------|-----------------------------------------------------------------------------|
   | **YouTube Data API (Google Cloud)** | Retrieves channel, video, and comment data. |
   | **Apify Actors & Dataset API** | Transcribes YouTube video content. |
   | **OpenAI GPT-4 & Vision API** | Analyzes text and images (like thumbnails). |
   | **PostgreSQL (LangChain Memory)** | Maintains long-term chat history for personalized interactions. |
   
   ---
   
   ### Final Thoughts
   
   This AI-powered YouTube assistant built with n8n captures the future of content intelligence: fast, automated, and deeply insightful. Whether you're a creator, marketer, or researcher, tools like this let you understand your audience on a deeper level—without the manual effort.
   
   Thanks to the power of n8n and the thoughtful integrations across APIs, creators can now access actionable insights in just minutes.
   
   Want to try it? Explore the workflow courtesy of [Mark Shcherbakov](https://www.linkedin.com/in/marklowcoding/) and the 5minAI community.
   
   👉 [Download or clone the workflow on n8n.io](https://n8n.io)
   
   ---
   
   If you found this useful, consider joining the [5minAI Skool Community](https://www.skool.com/5minai) where automations like this are made every day—often in 5 minutes or less.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.