MCP YouTube Extract

MCP YouTube Extract is a ready‑to‑use Model Context Protocol server that gives AI assistants instant access to YouTube video data without the need for a paid API key. By leveraging open‑source libraries and , the server can pull rich metadata (title, description, channel name, publish date, view count) and transcripts—including both manually created captions and auto‑generated ones—directly from a YouTube URL. This eliminates the friction of traditional API integration, making it ideal for rapid prototyping and low‑cost deployments.

What Problem Does It Solve?

Developers building AI workflows often need contextual information from video content to answer questions, summarize videos, or generate subtitles. Traditional solutions require managing API keys, handling quota limits, and dealing with complex authentication flows. MCP YouTube Extract removes these hurdles by providing a simple, key‑less interface that can be queried through the MCP tool protocol. It also offers graceful error handling and fallback logic for transcript retrieval, ensuring that even videos without captions can still be processed.

Core Functionality and Value

• Metadata Extraction: Retrieve comprehensive video details in a single call, enabling AI assistants to answer queries about the video's background or statistics.
• Transcript Retrieval: Fetch human‑written or auto‑generated transcripts, which can be used for summarization, keyword extraction, or generating closed captions.
• Robust Logging: Every request and response is logged in detail, facilitating debugging and auditability within larger AI pipelines.
• Error Handling & Fallback: If the primary transcript source fails, the server automatically attempts alternative methods, reducing the chance of silent failures.

These capabilities give developers a powerful, plug‑and‑play tool that can be integrated into any MCP‑compliant AI assistant with minimal effort.

Use Cases & Real‑World Scenarios

• Content Summarization: An AI assistant can quickly generate a concise summary of any YouTube video by pulling its transcript and metadata.
• Educational Tools: Build tutors that fetch lecture videos, extract key points, and provide study guides without needing to manage YouTube API quotas.
• Search & Discovery: Enhance search engines by adding video metadata to indexed results, allowing richer queries like “videos about quantum computing with over 1M views.”
• Compliance & Moderation: Automatically retrieve captions to check for policy violations or generate compliance reports.

Integration with AI Workflows

The server exposes its functionality through MCP tools, so any AI assistant that supports the protocol can call:

1. – returns a structured JSON object with video details.
2. – returns the transcript text or an error message if unavailable.

These tools can be chained with other MCP services (e.g., language models, summarization engines) to build sophisticated end‑to‑end pipelines. Because the server requires no API key by default, it can be deployed in isolated environments or on edge devices where external network access is limited.

Unique Advantages

• Zero‑Configuration Operation: Out of the box, no API key or environment setup is required, making it highly accessible for quick experiments.
• Open‑Source Underpinnings: Built on well‑maintained libraries that respect YouTube’s terms of service while providing reliable data extraction.
• Extensibility: The server’s modular design allows developers to add custom tools or logging hooks without touching the core logic.

In summary, MCP YouTube Extract turns any AI assistant into a powerful video intelligence engine with minimal setup, enabling developers to focus on building value‑adding features rather than wrestling with API logistics.