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MalikElate

YouTube Transcript Extractor MCP

by MalikElate
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

YouTube 대본 추출기 MCP 🎥

AI 비서가 YouTube 동영상에서 대본을 추출할 수 있도록 하는 모델 컨텍스트 프로토콜(MCP) 서버입니다. Cursor 및 Claude Desktop과 통합되도록 설계된 이 도구를 통해 AI는 YouTube 동영상 콘텐츠를 직접 분석하고 작업할 수 있습니다.

특징

  • 🎯 모든 공개 YouTube 비디오에서 대본 추출

  • 🔌 Cursor 및 Claude Desktop과의 간편한 통합

  • 🚀 유형 안전을 위해 TypeScript로 구축됨

  • 📦 간단한 설정 및 배포

  • 🛠️ 모델 컨텍스트 프로토콜 기반

Related MCP server: YouTube Translate MCP

필수 조건

  • Node.js(v16 이상)

  • pnpm(권장) 또는 npm

  • YouTube 비디오 URL을 추출하여 대본을 추출합니다.

설치

  1. 저장소를 복제합니다.

지엑스피1

  1. 종속성 설치:

pnpm install

  1. 프로젝트를 빌드하세요:

pnpm run build

구성

커서용

  1. 커서 설정 열기

  2. MCP로 이동 → 새 MCP 서버 추가

  3. 다음 설정으로 구성하세요.

    • 이름: youtube-transcript

    • 유형: command

    • 명령어: node /absolute/path/to/yt-mcp/build/index.js

클로드 데스크탑용

Claude Desktop 구성에 다음 구성을 추가하세요.

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "node",
      "args": ["/absolute/path/to/yt-mcp/build/index.js"]
    }
  }
}

용법

설정이 완료되면 AI는 비디오 URL로 도구를 호출하여 YouTube 비디오에서 대본을 추출할 수 있습니다. 예:

// The AI will use this format internally
const transcript = await extractTranscript({
  input: "https://www.youtube.com/watch?v=VIDEO_ID"
});

기술적 세부 사항

서버는 다음을 사용하여 구축되었습니다.

제한 사항

  • 공개 YouTube 동영상에서만 작동합니다.

  • 비디오에는 캡션/자막이 활성화되어 있어야 합니다.

  • 일부 비디오에는 100% 정확하지 않을 수 있는 자동 생성된 자막이 있을 수 있습니다.

문제 해결

일반적인 문제 및 해결책:

  1. "비디오 ID를 찾을 수 없습니다" 오류

    • YouTube URL이 완전하고 정확한지 확인하세요.

    • 영상이 공개적으로 접근 가능한지 확인하세요

  2. "사용 가능한 대본이 없습니다" 오류

    • 비디오에 자막이 활성화되어 있는지 확인하세요

    • 도구가 작동하는지 확인하려면 다른 비디오를 시도하세요.

  3. 빌드 오류

    • 모든 종속성이 설치되었는지 확인하세요

    • Node.js 버전을 확인하세요(v16 이상이어야 함)

기여하다

기여를 환영합니다! 풀 리퀘스트를 제출해 주세요. 주요 변경 사항의 경우, 먼저 이슈를 열어 변경 사항을 논의해 주세요.

특허

MIT

Available Tools

1 tool
youtube-transcript-extractorC

Extracts the transcript of a YouTube video.

ParametersJSON Schema
NameRequiredDescriptionDefault
inputYesa youtube video url

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Extracts' implies a read operation, it lacks details on permissions, rate limits, error handling, or output format. This leaves significant gaps in understanding the tool's behavior beyond its basic function.

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: 'Extracts the transcript of a YouTube video.' It is front-loaded with the core purpose and contains no unnecessary words, making it highly concise and well-structured.

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 and no output schema, the description is incomplete. It lacks information on behavioral traits (e.g., error cases, rate limits) and output details (e.g., transcript format, structure). While concise, it does not provide enough context for an agent to use the tool effectively beyond basic 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?

The input schema has 100% description coverage, with the parameter 'input' documented as 'a youtube video url.' The description does not add any meaning beyond this, such as URL format examples or validation rules. Given the high schema coverage, the baseline score of 3 is appropriate.

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: 'Extracts the transcript of a YouTube video.' It specifies the verb ('Extracts') and resource ('transcript of a YouTube video'), making the function unambiguous. However, with no sibling tools mentioned, there's no opportunity to differentiate from alternatives, preventing a perfect score.

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 for its 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.

  1. 1 tool update
    • First observedyoutube-transcript-extractor
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

B3.1/5.0

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 singular and clearly defined, so an agent cannot misselect among multiple options.

Naming Consistency5/5

The single tool name follows a clear verb-noun pattern (youtube-transcript-extractor), and with no other tools to compare, consistency is inherently perfect. There are no deviations or mixed conventions to evaluate.

Tool Count2/5

One tool is too few for a server that appears to handle YouTube transcript extraction, as it lacks complementary operations like listing videos, handling errors, or supporting multiple formats. This minimal scope may limit agent workflows and feels incomplete for the domain.

Completeness2/5

The server is severely incomplete for YouTube transcript extraction, as it only provides extraction without supporting operations like validation, search, or handling different transcript types. This creates significant gaps that could cause agent failures in real-world scenarios.

Maintenance

ActivityInactive
ResponsivenessNo issues

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