Quickly tap into the world’s largest video library to search YouTube, pull detailed video and channel data, or fetch comments and playlists - all with simple natural language prompts.
Scrape and analyze videos from YouTube’s 2B+ monthly users, complete with rich metadata, statistics, and comments in one place.

What is YouTube MCP?

When you create a YouTube node with AI, Gumloop builds a custom node that already understands Apify’s YouTube Scraper. Describe the result you need in plain English and the node maps your prompt to the right API call, returns clean structured data, and is ready to reuse in any workflow.

What Can It Do for You?

  • Discover fresh, high-performing videos for competitive research or content inspiration
  • Enrich any video URL with views, likes, duration, tags, and more
  • Pull an entire channel or playlist into Google Sheets for batch analysis
  • Capture real user comments for sentiment analysis, product feedback, or testimonial mining

Available Tools

ToolWhat It DoesExample Use
Search VideosSearch YouTube by keyword with filters like upload date, type, and video length. Returns title, URL, views, and more.”Search videos about ‘Python pandas tutorial’ uploaded after 2024-01-01, return title, url, view_count, publish_date”
Get Video DetailsFetch full metadata for a specific video by URL or ID, including statistics and content details.”Get details for https://youtube.com/watch?v=dQw4w9WgXcQ, return title, channel_name, view_count, like_count, published_at”
Get Channel VideosList videos from a channel with complete metadata. Supports sorting and limits.”Get videos from channel ‘@MrBeast’, limit 10, sort by most_popular, return title, url, view_count”
Get Playlist VideosRetrieve videos in a playlist with video-level data and playlist context.”Get videos from playlist ‘Learn React - Full Course’ by freeCodeCamp, limit 20, return title, url, duration”
Get Channel DetailsReturn channel-level stats such as subscriber count, total videos, description, and creation date.”Get channel details for ‘@mkbhd’, return channel_name, subscriber_count, total_videos, description”
Get Video CommentsCollect comments from a video with author info, likes, and reply counts.”Get top 30 comments for video titled ‘iPhone 15 Review’ by MKBHD, return author, comment_text, like_count, published_time”

Credit Costs

ToolCredits Per Use
Search Videos3 credits per item
Get Video Details4 credits per item
Get Channel Videos3 credits per item
Get Playlist Videos3 credits per item
Get Channel Details5 credits per item
Get Video Comments5 credits per item

How to Use

1

Create Your YouTube MCP Node

Go to your node library, search for YouTube, and click “Create a node with AI”
2

Add Your Prompt

Drag the YouTube node onto the canvas and describe the single action you want it to perform.
3

Test Your Node

Run the node. Review the output to confirm it contains the fields you requested.
4

Save and Reuse

Save the working node to your library and drop it into any future workflow.

Example Prompts

Here are some prompts that work well with YouTube MCP: Search for Trend Analysis
Search videos about "AI prompting tips" uploaded in the past 30 days, return title, url, view_count, publish_date
Enrich a Specific Video
Get details for a given YouTube URL, return title, channel_name, duration, tags, view_count
Pull a Channel’s Latest Content
Get channel videos for the channel URL, limit 20, sort by most_recent, return title, url, publish_date
Grab Playlist Items
Get playlist videos from a provided playlist URL, limit 25, return title, url, duration
Channel Overview
Get channel details from a given Channel URL, return channel_name, subscriber_count, total_videos, description
Fetch Comments for Sentiment
Get video comments given a YouTube video URL, limit 50, return author, comment_text, like_count
Start with a narrow filter and small limit (for example, “limit 10”) to preview the structure, then increase the limit once you are happy with the fields.

Troubleshooting

If your YouTube MCP node isn’t behaving as expected, try these best practices:

Keep Prompts Simple and Specific

  • Good: “Search videos about ‘Stock market analysis’ uploaded after 2025-01-01, return title, url”
  • Bad: “Search for the top stock market videos, and summarize each video”
While the complex prompt may work, it is more efficient to break it into separate nodes. YouTube MCP works best with focused, single-action prompts.

Match What YouTube Can Do

  • Good: “Get video comments for Video URL, limit 20, return author, comment_text”
  • Bad: “Download the video, transcribe it, and translate the transcript to French”
YouTube MCP excels at data retrieval. For transcription or translation, connect it to an appropriate node like an Ask AI node in your workflow.

Break Complex Tasks Into Steps

Instead of trying to do everything in one prompt (which can cause timeouts and errors):
Search videos about electric cars, summarize each video, categorize the sentiment, and post the best ones to Slack
Break this into smaller, focused nodes that each handle one task:
1

Step 1: Search Videos

Search videos about electric cars uploaded in August 2025, limit 50, return title, url, view_count
2

Step 2: Fetch Transcript

Given a video URL fetch the video transcript
3

Step 3: Categorize Sentiment using the AI Categorizer node

Classify each transcript as positive, neutral, or negative (Categorizer)
4

Step 4: Share to Slack using the 'Slack Message Sender' node

Send positive summaries to the #ev-insights Slack channel (Slack Message Sender)
In your workflow, connect these nodes sequentially. The video URLs from Step 1 feed into Step 2, sentiment labels from Step 3 determine which summaries are sent in Step 4.

Focus on Data Retrieval

YouTube MCP is great at getting information from YouTube. For analysis or content creation, pair it with other nodes. Example:
  • Good prompt: “Get playlist videos for PL12345, return title, duration”
  • Bad prompt: “Get playlist videos, write a blog post summarizing each one, and publish it to WordPress”
Use Ask AI for writing and a Call API or Run Code node to publish content. Keep the YouTube node focused on data extraction.

Troubleshooting Node Creation

Need More Help?