MCP Server for YouTube Data Extraction

Use Bright Data’s enterprise-grade MCP Server to scrape public YouTube data. Extract, analyze, and process video, channel, playlist, and comment data at scale—fast, reliable, and resilient.

Get StartedTry the Playground
No credit card required

The Ultimate MCP Tool to Scrape YouTube Data

Get Started Check the Repo

Want to try the YouTube MCP without setting up anything?

Visit playground on Smithery

One MCP for the Web

Bright Data MCP for YouTube lets you extract public video, channel, playlist, and comment data, trending videos, engagement, and analytics—no blocks, at any scale.
Search
  • Find videos by keyword, channel, or playlist
  • Extract video titles, URLs, views, likes, and tags
  • Get published dates, thumbnails, and durations
Crawl
  • Crawl channels, subscriber data, and full video libraries
  • Export comments, playlist content, and live chat logs
  • Monitor trending, recommended, or related videos
Access
  • Access public YouTube data across regions
  • Bypass anti-bot, geo, and JavaScript challenges
  • Get real-time video stats, viability, and premieres
Navigate
  • Automate browsing of channels, playlists, and video feeds
  • Bulk-extract comments, likes, and engagement metrics
  • Mimic viewer behavior to avoid detection
Get Started Check the Repo
get inspired

See what people are building

Discover more

Ready to Supercharge YouTube Scraping?

Get started with YouTube MCP Server in minutes. No setup required.

Try it now
No credit card required

YouTube MCP Server FAQs

The YouTube MCP Server is a specialized integration that empowers your AI agents to access real-time public data from YouTube. It acts as a bridge, allowing tools like Claude, Cursor, and custom LLMs to search, extract, and interact with YouTube content dynamically.

Built on Bright Data's robust infrastructure, the Web MCP Server handles the complexities of web data extraction behind the scenes. It automatically manages proxy rotation, CAPTCHA solving, and unlocking technology to ensure your AI receives structured, reliable data from YouTube without getting blocked.

The data is completely real-time. Unlike databases that can become outdated, the YouTube MCP fetches live content directly from the source at the moment of request, ensuring your AI agents act on the most current pricing, posts, or profile information available.

Yes! We offer a generous free tier that includes 5,000 requests per month. This allows developers and businesses to test the YouTube MCP Server, build prototypes, and perform light data extraction at no cost before scaling up.

Yes. Beyond retrieving static data, the server supports full browser automation. Your agents can be instructed to navigate YouTube pages, click buttons, handle infinite scrolling, and even take screenshots, enabling complex workflows that simulate real user behavior.

You have the choice. You can use our fully managed Remote MCP for instant access with zero infrastructure setup, or you can deploy the Local MCP if you require on-premise control and custom environment configurations for your YouTube projects.

Our Web MCP Server is designed for seamless integration with popular AI clients. It works natively with Claude Desktop, Cursor, Windsurf, and diverse agentic frameworks like LangChain, making it easy to add YouTube data capabilities to your existing workflows.

Rapid mode is free and ideal for everyday tasks like SERP lookups and basic text extraction. Pro mode unlocks premium capabilities for YouTube, including deep structured data extraction and advanced browser automation tools designed for large-scale production environments.

Absolutely. The YouTube MCP Server is built with strict adherence to data protection regulations, including GDPR and CCPA. We only access publicly available web data, ensuring your AI operations remain compliant and ethically sound.

The server delivers data in clean, AI-ready formats. Depending on your specific needs, you can retrieve YouTube data as structured JSON objects for precise analysis or as simplified Markdown text optimized for LLM context windows.