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YouTube MCP Server

by nattyraz
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TypeScript
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YouTube MCP サーバー

YouTube動画を操作するためのモデルコンテキストプロトコル（MCP）サーバー。このサーバーは、動画のメタデータやキャプションを抽出し、様々なテンプレートを使用してマークダウン形式に変換するためのツールを提供します。

特徴

  • ビデオメタデータ: 包括的なビデオ情報を取得します

  • キャプション抽出:自動生成および手動キャプションのサポート

  • 複数の言語：英語とフランス語のサポートが組み込まれています

  • テンプレート システム: 3 つの組み込みマークダウン テンプレート:

    • 基本: シンプルなトランスクリプト形式

    • 詳細: タイムスタンプ付きの完全なメタデータ

    • 検索: コンテキストに応じた結果の強調表示

  • 検索機能: 動画のキャプション内を検索

  • 柔軟な認証: APIキーとOAuth2認証の両方をサポート

Related MCP server: YouTube Video Summarizer MCP Server

前提条件

  • Node.js (v16 以上)

  • npmまたはyarn

  • YouTube Data API キーおよび/または OAuth2 認証情報

インストール

  1. リポジトリをクローンします。

git clone [repository-url]
cd youtube-mcp

  1. 依存関係をインストールします:

npm install

  1. プロジェクトをビルドします。

npm run build

構成

YouTube の認証情報を使用して、ルート ディレクトリに.envファイルを作成します。

YOUTUBE_API_KEY=your_api_key
YOUTUBE_CLIENT_ID=your_client_id
YOUTUBE_CLIENT_SECRET=your_client_secret
YOUTUBE_REFRESH_TOKEN=your_refresh_token  # Optional, for OAuth2

MCP構成

サーバーを MCP 設定ファイル (通常は~/.config/Code/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json ) に追加します。

{
  "mcpServers": {
    "youtube": {
      "command": "node",
      "args": ["path/to/youtube-mcp/build/index.js"],
      "env": {
        "YOUTUBE_API_KEY": "your_api_key",
        "YOUTUBE_CLIENT_ID": "your_client_id",
        "YOUTUBE_CLIENT_SECRET": "your_client_secret"
      },
      "disabled": false,
      "alwaysAllow": []
    }
  }
}

使用法

サーバーは次のツールを提供します。

1. ビデオ情報を取得する

use_mcp_tool youtube get_video_info {
  "url": "https://www.youtube.com/watch?v=VIDEO_ID"
}

2. 字幕を取得する

use_mcp_tool youtube get_captions {
  "url": "https://www.youtube.com/watch?v=VIDEO_ID",
  "language": "en"  // Optional, defaults to "en"
}

3. Markdownに変換する

use_mcp_tool youtube convert_to_markdown {
  "url": "https://www.youtube.com/watch?v=VIDEO_ID",
  "template_name": "detailed",  // Optional, "basic", "detailed", or "search"
  "language": "en",            // Optional
  "options": {                 // Optional
    "include_chapters": true,
    "search_term": "keyword"   // Only for search template
  }
}

4. リストテンプレート

use_mcp_tool youtube list_templates

依存関係

{
  "dependencies": {
    "@modelcontextprotocol/sdk": "latest",
    "googleapis": "^146.0.0",
    "google-auth-library": "^9.0.0",
    "youtube-captions-scraper": "^2.0.0",
    "express": "^4.18.2",
    "open": "^9.1.0"
  },
  "devDependencies": {
    "@types/node": "^20.0.0",
    "typescript": "^5.0.0",
    "tsx": "^4.0.0"
  }
}

OAuth2のセットアップ

OAuth2 認証の場合（プライベート ビデオ アクセスに必要）：

  1. Google Cloud Consoleでプロジェクトを作成する

  2. YouTube Data API v3 を有効にする

  3. OAuth2 認証情報を作成する (Web アプリケーション タイプ)

  4. 認証スクリプトを実行します。

node src/get-api-key.js

  1. ブラウザの指示に従ってアプリケーションを承認します

  2. リフレッシュトークンを構成にコピーします

テンプレートのカスタマイズ

src/index.tsのDEFAULT_TEMPLATES配列を変更することで、カスタムテンプレートを追加できます。テンプレートは以下の構造に従います。

interface MarkdownTemplate {
  name: string;
  description: string;
  format: {
    header?: string;
    chapter_format?: string;
    caption_block: string;
    timestamp_format?: string;
    search_result_format?: string;
  }
}

ライセンス

マサチューセッツ工科大学

貢献

  1. リポジトリをフォークする

  2. 機能ブランチを作成します（ git checkout -b feature/amazing-feature ）

  3. 変更をコミットします ( git commit -m 'Add some amazing feature' )

  4. ブランチにプッシュする ( git push origin feature/amazing-feature )

  5. プルリクエストを開く

Available Tools

1 tool
get_transcriptC

YouTubeの字幕をURLまたは動画IDから取得します

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube動画のURLまたはID
langYes字幕の言語コード（例: 'ja', 'en'）en

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 full burden for behavioral disclosure. It mentions retrieving transcripts but doesn't describe what happens if no transcript exists, rate limits, authentication requirements, error conditions, or the format/scope of returned data. This leaves significant behavioral gaps for a tool that interacts with external APIs.

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

Conciseness5/5

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

The description is a single, efficient sentence in Japanese that clearly communicates the core functionality without any wasted words. It's appropriately sized and front-loaded with the essential information.

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?

For a tool with no annotations, no output schema, and interaction with an external service (YouTube), the description is insufficient. It doesn't explain what format the transcript returns, error handling, availability constraints, or any behavioral aspects needed for reliable use by an AI agent.

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 already fully documents both parameters (url and lang with their descriptions and default). The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score for high schema coverage.

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 action ('取得します' - get/retrieve) and resource ('YouTubeの字幕' - YouTube subtitles/transcripts) with the input source specified ('URLまたは動画IDから' - from URL or video ID). It's specific about what the tool does, though it doesn't need to distinguish from siblings since there are none.

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 limitations. It simply states what the tool does without context about appropriate use cases or constraints.

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.

  1. 1 tool update
    • First observedget_transcript
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear and distinct purpose focused on retrieving transcripts from YouTube.

Naming Consistency5/5

A single tool inherently has perfect naming consistency as there are no other tools to compare it against. The tool name 'get_transcript' follows a clear verb_noun pattern.

Tool Count2/5

One tool is too few for a server named 'YouTube MCP Server', which suggests a broader scope. A single transcript retrieval tool feels incomplete for typical YouTube operations like searching videos, listing playlists, or managing uploads.

Completeness1/5

The tool surface is severely incomplete for a YouTube server. It only covers transcript retrieval, with no tools for core YouTube functionalities such as video search, metadata retrieval, playlist management, or user interactions, leaving significant gaps.

Maintenance

ActivityInactive
ResponsivenessNo issues

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