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nabid-pf

YouTube Video Summarizer MCP Server

by nabid-pf
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TypeScript
Remote

YouTube Video Summarizer MCP Server

An MCP (Model Context Protocol) server that enables AI assistants to analyze and summarize YouTube videos by extracting captions, descriptions, and metadata.

Features

  • Extract video captions/subtitles in multiple languages

  • Retrieve comprehensive video metadata (title, description, duration)

  • Provide structured data to AI assistants for comprehensive video summarization

  • Works with any MCP-compatible client through MCP integration

  • Support for multiple YouTube URL formats

  • Language-specific caption extraction

Related MCP server: YouTube DLP MCP Server

Integrating with MCP Clients

To add the MCP server to your MCP client, you can use either method:

Option 1: Using npx (No Installation Required)

Add the following to your MCP client configuration file:

{
  "mcpServers": {
    "youtube-video-summarizer": {
      "command": "npx",
      "args": ["-y", "youtube-video-summarizer-mcp"]
    }
  }
}

The server automatically filters out any npm/npx output to ensure MCP protocol compliance.

Option 2: Global Installation (Recommended for Production)

  1. Install the package globally:

    npm install -g youtube-video-summarizer-mcp

  2. Add the following to your MCP client configuration file:

{
  "mcpServers": {
    "youtube-video-summarizer": {
      "command": "youtube-video-summarizer",
      "args": []
    }
  }
}

Available Tools

When integrated with an MCP client, the following commands become available:

  • get-video-info-for-summary-from-url: Extract video information and captions from a YouTube URL

  • get-video-captions: Get captions/subtitles for a specific video

  • get-video-metadata: Retrieve comprehensive video metadata

Usage Examples

Once integrated with your MCP client, you can use natural language to request video summaries:

"Can you summarize this YouTube video: https://youtube.com/watch?v=VIDEO_ID"
"What are the main points from this video's captions?"
"Extract the key information from this YouTube link"

Installation

npm install -g youtube-video-summarizer-mcp

Development

git clone https://github.com/nabid-pf/youtube-video-summarizer-mcp.git
cd youtube-video-summarizer-mcp
npm install
npm run build

How It Works

  1. URL Parsing: Extracts video IDs from various YouTube URL formats

  2. Caption Extraction: Uses youtube-caption-extractor to get subtitles

  3. Metadata Retrieval: Fetches video title, description, and other details

  4. MCP Integration: The Model Context Protocol (MCP) to communicate with AI assistants

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Available Tools

1 tool
get-video-info-for-summary-from-urlC

Get details or explanation about a YouTube video, get captions or subtitles of Youtube video from a URL

ParametersJSON Schema
NameRequiredDescriptionDefault
videoUrlYesThe URL or ID of the YouTube video
languageCodeNoThe language code of the video

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool can 'get details or explanation' and 'get captions or subtitles', but fails to specify permissions needed, rate limits, error conditions, or output format. For a tool that likely involves external API calls, this lack of transparency is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded, consisting of a single sentence that efficiently communicates the core functionality. However, it could be slightly more structured by separating the two distinct purposes (details vs. captions) for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of interacting with YouTube videos (likely involving external APIs), no annotations, and no output schema, the description is incomplete. It lacks crucial information about behavioral traits, error handling, and what the return values entail, making it inadequate for confident tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents both parameters (videoUrl and languageCode). The description adds no additional meaning beyond what the schema provides, such as format examples or usage notes for the parameters, resulting in the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('get details or explanation', 'get captions or subtitles') and identifies the resource ('YouTube video from a URL'). It distinguishes between two related but distinct functions (details/explanation vs. captions/subtitles), though without sibling tools to differentiate from, it cannot achieve a perfect 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It merely lists what the tool does without context for application, leaving the agent to infer usage scenarios independently.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 1 tool updatev1.8.7
    • First observedget-video-info-for-summary-from-url
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TDQS

B3.1/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined as retrieving video details and captions for summarization from a YouTube URL.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect. The tool name uses a clear verb-noun pattern (get-video-info-for-summary-from-url) that is descriptive and follows a logical structure.

Tool Count2/5

A single tool is too few for a server named 'YouTube Video Summarizer MCP Server', as it suggests a broader summarization functionality. The tool only fetches video info and captions, lacking operations like generating summaries, processing text, or managing multiple videos, making the scope feel incomplete and thin.

Completeness2/5

The tool set is severely incomplete for the server's purpose. It only provides video details and captions, but does not include any summarization tools (e.g., generate-summary, analyze-captions) or related operations (e.g., list-videos, save-summary), leaving obvious gaps that will hinder agent workflows.

Maintenance

ActivityInactive
ResponsivenessSyncing

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