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sinco-lab

mcp-youtube-transcript

by sinco-lab
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TypeScript
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MCP YouTube 대본 서버

대장간 배지

YouTube 동영상의 대본을 검색할 수 있는 모델 컨텍스트 프로토콜 서버입니다. 이 서버는 간단한 인터페이스를 통해 동영상 대본에 직접 접근할 수 있도록 하여 콘텐츠 분석 및 처리에 이상적입니다.

목차

Related MCP server: YouTube Transcript Server

특징

✨ 주요 기능:

  • YouTube 동영상에서 대본 추출

  • 여러 언어 지원

  • 연속 모드 또는 단락 모드로 텍스트 서식 지정

  • 비디오 제목 및 메타데이터 검색

  • 자동 문단 분할

  • 텍스트 정규화 및 HTML 엔터티 디코딩

  • 강력한 오류 처리

  • 타임스탬프 및 중복 감지

시작하기

필수 조건

  • Node.js 18 이상

설치

두 가지 설치 방법이 제공됩니다.

옵션 1: 수동 구성(프로덕션에 권장)

  1. Claude Desktop 구성 파일을 생성하거나 편집합니다.

    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

    • Windows: %APPDATA%\Claude\claude_desktop_config.json

  2. 다음 구성을 추가합니다.

지엑스피1

macOS용 빠른 설정 스크립트:

# Create directory if it doesn't exist
mkdir -p ~/Library/Application\ Support/Claude

# Create or update config file
cat > ~/Library/Application\ Support/Claude/claude_desktop_config.json << 'EOL'
{
  "mcpServers": {
    "youtube-transcript": {
      "command": "npx",
      "args": [
        "-y",
        "@sinco-lab/mcp-youtube-transcript"
      ]
    }
  }
}
EOL

옵션 2: Smithery 경유(개발 전용)

npx -y @smithery/cli install @sinco-lab/mcp-youtube-transcript --client claude

⚠️ 참고 : 이 방법은 Smithery의 프록시 서비스에 의존하므로 프로덕션 용도로는 권장되지 않습니다.

용법

기본 구성

Claude Desktop/Cursor/cline과 함께 사용하려면 구성이 다음과 일치하는지 확인하세요.

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "npx",
      "args": ["-y", "@sinco-lab/mcp-youtube-transcript"]
    }
  }
}

테스트

클로드 앱으로

  1. 설치 후 Claude 앱을 다시 시작하세요

  2. 간단한 명령으로 테스트해 보세요:

    https://www.youtube.com/watch?v=AJpK3YTTKZ4 Summarize this video

출력 예:데모

MCP 검사관과 함께

# Clone and setup
git clone https://github.com/sinco-lab/mcp-youtube-transcript.git
cd mcp-youtube-transcript
npm install
npm run build

# Launch inspector
npx @modelcontextprotocol/inspector node "dist/index.js"

# Access http://localhost:6274 and try these commands:
# 1. List Tools: clink `List Tools`
# 2. Test get_transcripts with:
#    url: "https://www.youtube.com/watch?v=AJpK3YTTKZ4"
#    lang: "en" (optional)
#    enableParagraphs: false (optional)

문제 해결 및 유지 관리

클로드 로그 확인

Claude의 로그를 모니터링하려면 다음 명령을 사용할 수 있습니다.

tail -n 20 -f ~/Library/Logs/Claude/mcp*.log

이렇게 하면 로그 파일의 마지막 20줄이 표시되고, 새로운 항목이 추가되면 계속해서 표시됩니다.

참고 : Claude 앱은 MCP 서버 로그 파일에 자동으로 mcp-server- 를 붙입니다. 예를 들어, 저희 서버 로그는 mcp-server-youtube-transcript.log 에 기록됩니다.

npx 캐시 정리

npx 캐시와 관련된 문제가 발생하면 다음을 사용하여 수동으로 캐시를 정리할 수 있습니다.

rm -rf ~/.npm/_npx

이렇게 하면 캐시된 패키지가 제거되고 처음부터 다시 시작할 수 있습니다.

API 참조

성적증명서 받기

YouTube 동영상에서 대본을 가져옵니다.

매개변수:

  • url (문자열, 필수): YouTube 비디오 URL 또는 ID

  • lang (문자열, 선택 사항): 언어 코드(기본값: "en")

  • enableParagraphs (부울, 선택 사항): 문단 모드 활성화(기본값: false)

응답 형식:

{
  "content": [{
    "type": "text",
    "text": "Video title and transcript content",
    "metadata": {
      "videoId": "video_id",
      "title": "video_title",
      "language": "transcript_language",
      "timestamp": "processing_time",
      "charCount": "character_count",
      "transcriptCount": "number_of_transcripts",
      "totalDuration": "total_duration",
      "paragraphsEnabled": "paragraph_mode_status"
    }
  }]
}

개발

프로젝트 구조

├── src/
│ ├── index.ts            # Server entry point
│ ├── youtube.ts          # YouTube transcript fetching logic
├── dist/                 # Compiled output
└── package.json

주요 구성 요소

  • YouTubeTranscriptFetcher : 핵심 대본 가져오기 기능

  • YouTubeUtils : 텍스트 처리 및 유틸리티

특징 및 역량

  • 오류 처리:

    • 잘못된 URL/ID

    • 사용할 수 없는 대본

    • 언어 사용 가능 여부

    • 네트워크 오류

    • 속도 제한

  • 텍스트 처리:

    • HTML 엔티티 디코딩

    • 구두점 정규화

    • 공간 정규화

    • 스마트 문단 감지

기여하다

여러분의 참여를 환영합니다! 이슈를 제출하거나 풀 리퀘스트를 보내주세요.

특허

이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다. 자세한 내용은 라이선스 파일을 참조하세요.

관련 프로젝트

Available Tools

1 tool
get_transcriptsA

Extract and process transcripts from a YouTube video.

Parameters:

  • url (string, required): YouTube video URL or ID.

  • lang (string, optional, default 'en'): Language code for transcripts (e.g. 'en', 'uk', 'ja', 'ru', 'zh').

  • enableParagraphs (boolean, optional, default false): Enable automatic paragraph breaks.

IMPORTANT: If the user does not specify a language code, DO NOT include the lang parameter in the tool call. Do not guess the language or use parts of the user query as the language code.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL or ID
langNoLanguage code for transcripts, default 'en' (e.g. 'en', 'uk', 'ja', 'ru', 'zh')en
enableParagraphsNoEnable automatic paragraph breaks, default `false`

TDQS

A3.8/5.0
Behavior4/5

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 effectively explains the tool's core function and includes important behavioral guidance about parameter handling (the IMPORTANT note about not guessing language). However, it doesn't mention potential limitations like video availability, transcript existence, rate limits, or error conditions.

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 well-structured with a clear purpose statement followed by parameter documentation and important usage notes. Every sentence serves a purpose, though the parameter list slightly duplicates schema information. The IMPORTANT section is appropriately emphasized for critical behavioral guidance.

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

Completeness3/5

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

Given no annotations and no output schema, the description provides adequate coverage for the tool's basic function and parameters. However, it lacks information about return values, error handling, and operational constraints that would be helpful for an agent. The IMPORTANT note adds valuable context, but more behavioral transparency would improve completeness.

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 documents all parameters thoroughly. The description repeats this information in a bulleted list without adding significant semantic context beyond what's in the schema. The IMPORTANT note about language parameter handling adds some value, but overall the description doesn't enhance parameter understanding beyond the structured schema.

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

Purpose5/5

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 ('extract and process') and resource ('transcripts from a YouTube video'). It distinguishes itself from potential alternatives by focusing on transcript extraction rather than other video-related operations, though no sibling tools exist for direct comparison.

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

Usage Guidelines3/5

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

The description provides some usage guidance through the IMPORTANT note about language parameter handling, but it doesn't explicitly state when to use this tool versus alternatives (e.g., when transcripts are needed vs. other video metadata). Since no sibling tools exist, this is less critical, but general context about appropriate use cases is missing.

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_transcripts
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

A3.7/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect. The tool name 'get_transcripts' follows a clear verb_noun pattern.

Tool Count2/5

A single tool is too few for a server focused on YouTube transcripts, as it lacks operations like searching transcripts, managing multiple videos, or handling errors. This minimal scope limits functionality and agent workflows.

Completeness2/5

The tool set is severely incomplete for the domain of YouTube transcript processing. It only provides extraction (get_transcripts), missing essential operations such as searching within transcripts, listing available languages, or handling video metadata, which are common needs in this context.

Maintenance

ActivityInactive
ResponsivenessNo issues

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