Build an AI Agent to Chat with YouTube (n8n Guide)

Unlock richer content insights and automate research with an AI agent that talks to YouTube. This guide explains a ready-to-use n8n workflow integrating the YouTube Data API, Apify, and OpenAI to fetch channel and video data, analyze comments, transcribe videos, and evaluate thumbnails.

Why build an AI agent for YouTube?

Creators, marketers, and product teams can benefit from automated analysis of YouTube channels and videos. An AI agent that processes comments, transcriptions, and thumbnails helps you:

• Discover viewer sentiment and pain points from comments.
• Repurpose video content faster using accurate transcriptions.
• Improve thumbnail and title performance with AI-driven design feedback.
• Automate repetitive data gathering so your team focuses on creative work.

What this workflow does (high-level)

The n8n workflow wires together a chat trigger and an intelligent agent that runs a set of tools depending on user input. Core capabilities include:

• Get channel details by handle/URL (channel_id, title, description).
• Search videos or list videos from a channel (with sorting options).
• Fetch video details (title, description, stats) and filter out shorts.
• Retrieve and aggregate comment threads for sentiment and insights.
• Transcribe videos via Apify (or another transcription provider).
• Analyze thumbnails and images using OpenAI’s image analysis tools.
• Persist chat memory in Postgres for conversational context.

Architecture & visual reference

The workflow uses an agent node to orchestrate tool calls. The Switch node directs commands like get_channel_details, video_details, comments, search, videos, analyze_thumbnail, and video_transcription. Each tool is implemented as an HTTP request or an n8n wrapper node. (See the diagram in the featured image for the layout.)

Prerequisites

• n8n instance (self-hosted or cloud)
• Google Cloud project with YouTube Data API enabled and an API key
• OpenAI API key (for text and image analysis)
• Apify (or another transcription service) API key for video-to-text
• Postgres database for chat memory (optional but recommended)
• Basic understanding of REST APIs and n8n nodes

Step-by-step setup

1. Create and configure API credentials

In Google Cloud, enable the YouTube Data API and create an API key. In OpenAI, create an API key and ensure your account has image analysis or multimodal access. Create an Apify token for transcription runs. Add these credentials to n8n credential manager and replace placeholders across all nodes.

2. Import the n8n workflow

Import the provided n8n workflow JSON/template into your n8n instance. The workflow includes the chat trigger, an OpenAI chat model node, a LangChain-style agent, the Switch router, and HTTP request nodes for all YouTube endpoints.

3. Configure the chat trigger and agent

Set the webhook for the chat trigger. Configure the agent node’s system prompt to act as a YouTube assistant and include instructions to call the right tools in order. Optionally point the agent at your Postgres memory node to preserve session state across conversations.

4. Update HTTP request nodes

Replace generic credentials in all HTTP request nodes (YouTube, Apify) with the credentials you created. Verify each request’s query parameters (for example, maxResults, part, and ordering).

5. Test common flows

Run scenarios like “get_channel_details” using a channel handle, or request “comments” with a video_id to validate pagination and response parsing. Ensure the Edit Fields node transforms comment replies into a clean response for the AI to analyze.

How the tools work together

Get channel and videos

The channel tool extracts the channel_id from a handle or channel URL. The videos tool requests a list of videos using channel_id and can sort by date or viewCount. Important: YouTube search returns shorts — use the video details tool to inspect contentDetails.duration and filter out videos shorter than 60 seconds if you don’t want shorts.

Comments aggregation and analysis

The Get Comments HTTP node pulls up to 100 comments per request. Implement pagination in the node or via the agent’s plan to iterate until all pages are collected. Use the Edit Fields node to flatten threads and combine top-level comments with replies into a single text blob the OpenAI model can analyze for themes, sentiment, and actionable insights.

Transcription

Send the video URL to an Apify transcription actor (or alternative). Apify returns the full text which you can analyze for topics, repurposing ideas, timestamps, and quoteable moments. Be mindful of transcription costs — long videos can be more expensive.

Thumbnail analysis

Provide the thumbnail URL to OpenAI’s image analysis or a similar service with a custom prompt (evaluate CTA clarity, color contrast, text prominence, face presence, and readability). The agent can return specific design suggestions to A/B test thumbnails faster.

Tips for production use

• Cache results for expensive API calls (video details, transcriptions) to reduce cost and latency.
• Implement rate-limit handling and exponential backoff for YouTube and OpenAI requests.
• Store and version the prompts you use for transcription cleanup and thumbnail critique so results are reproducible.
• Use pagination to fetch all comments — don’t rely on a single 100-result call for large videos.
• Filter out shorts by checking contentDetails.duration when loading video lists.

Common use cases

• Creator research: Understand trending feedback across rival channels.
• Community management: Automatically surface negative sentiment or feature requests.
• Content repurposing: Find quotable moments and chapter suggestions from transcriptions.
• Growth experiments: Test thumbnail recommendations and monitor CTR improvements.

Costs, quotas and limits

Be aware of the following:

• YouTube Data API quotas — heavy search/comment usage consumes quota quickly.
• OpenAI costs for text and image analysis depending on model and usage.
• Transcription provider pricing (Apify actor runs or third-party transcription services).

Troubleshooting checklist

• Unauthorized errors: verify API keys and n8n credentials.
• Empty comments: ensure video_id is correct and comments aren’t disabled for the video.
• Missing transcriptions: check Apify job status and input URL format.
• Agent stalls: review the agent system prompt and ensure tool names match the Switch node commands.

Next steps and call-to-action

Ready to automate YouTube insights? Import the n8n workflow, replace credentials, and run the sample queries in the pinData (search example included). If you want the ready-to-import workflow file, detailed setup scripts, or a walkthrough video, download the template or join the 5minAI community for hands-on help.

Get the workflow: Download the n8n template and replace Apify/OpenAI/Google credentials. Want a live walkthrough? Watch the setup video (13 min) or contact us for a custom integration.

If you’d like, I can:

• Provide the exact n8n JSON export adapted to your API keys (safely, without storing your keys).
• Create prompt templates for comment-sentiment and thumbnail feedback.
• Help configure Postgres chat memory and retention policy.

Drop a message with your use case (creator research, community monitoring, or growth experiments) and I’ll propose a tailored setup.