YouTube Transcript Server
YouTube 대본 서버
YouTube 동영상의 대본을 검색할 수 있는 모델 컨텍스트 프로토콜 서버입니다. 이 서버는 간단한 인터페이스를 통해 동영상 캡션과 자막에 직접 접근할 수 있도록 지원합니다.
Smithery를 통해 설치
Smithery 를 통해 Claude Desktop용 YouTube 대본 서버를 자동으로 설치하는 방법:
지엑스피1
구성 요소
도구
get_transcript
YouTube 동영상에서 대본 추출
입력:
url(문자열, 필수): YouTube 비디오 URL 또는 비디오 IDlang(문자열, 선택 사항, 기본값: "en"): 대본에 대한 언어 코드(예: 'ko', 'en')
Related MCP server: YouTube Transcript Extractor MCP
주요 특징
다양한 비디오 URL 형식 지원
언어별 대본 검색
응답의 자세한 메타데이터
구성
Claude Desktop과 함께 사용하려면 다음 서버 구성을 추가하세요.
{
"mcpServers": {
"youtube-transcript": {
"command": "npx",
"args": ["-y", "@kimtaeyoon83/mcp-server-youtube-transcript"]
}
}
}도구를 통해 설치
mcp-get 모델 컨텍스트 프로토콜(MCP) 서버를 설치하고 관리하기 위한 명령줄 도구입니다.
npx @michaellatman/mcp-get@latest install @kimtaeyoon83/mcp-server-youtube-transcript어썸-mcp-서버
awesome-mcp-servers 엄선된 멋진 모델 컨텍스트 프로토콜(MCP) 서버 목록입니다.
개발
필수 조건
Node.js 18 이상
npm 또는 yarn
설정
종속성 설치:
npm install서버를 빌드하세요:
npm run build자동 재빌드를 사용한 개발의 경우:
npm run watch테스트
npm test디버깅
MCP 서버는 stdio를 통해 통신하므로 디버깅이 어려울 수 있습니다. 개발에는 MCP Inspector를 사용하는 것이 좋습니다.
npm run inspector오류 처리
서버는 일반적인 시나리오에 대해 강력한 오류 처리를 구현합니다.
잘못된 비디오 URL 또는 ID
사용할 수 없는 대본
언어 가용성 문제
네트워크 오류
사용 예
비디오 URL로 대본 받기:
await server.callTool("get_transcript", {
url: "https://www.youtube.com/watch?v=VIDEO_ID",
lang: "en"
});비디오 ID로 대본 받기:
await server.callTool("get_transcript", {
url: "VIDEO_ID",
lang: "ko"
});Claude 데스크톱 앱에서 YouTube 자막을 추출하는 방법
chat: https://youtu.be/ODaHJzOyVCQ?si=aXkJgso96Deri0aB Extract subtitles보안 고려 사항
서버:
모든 입력 매개변수를 검증합니다
YouTube API 오류를 정상적으로 처리합니다.
전사본 검색을 위한 시간 초과를 구현합니다.
문제 해결을 위한 자세한 오류 메시지를 제공합니다.
특허
이 MCP 서버는 MIT 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 라이선스 파일을 참조하세요.
Available Tools
1 toolget_transcriptC
Extract transcript from a YouTube video URL or ID
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | YouTube video URL or ID | |
| lang | Yes | Language code for transcript (e.g., 'ko', 'en') | en |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions extraction but doesn't disclose behavioral traits like rate limits, authentication needs, error handling, or what happens if the video lacks a transcript. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error cases, or operational constraints, which are crucial for a tool that interacts with external services like YouTube. This leaves the agent with insufficient context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description implies parameters for URL/ID and language, but the input schema already has 100% coverage with clear descriptions for 'url' and 'lang'. The description adds minimal value beyond the schema, so it meets the baseline of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'extract' and the resource 'transcript from a YouTube video', making the purpose specific and understandable. However, with no sibling tools mentioned, it cannot differentiate from alternatives, so it doesn't reach the highest score of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 only states what the tool does, with no context for usage decisions.
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 tool update
- First observed
get_transcript
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as extracting transcripts from YouTube videos, making it distinct by default.
The single tool name follows a clear verb_noun pattern (get_transcript), which is consistent and predictable. There are no other tools to compare against, so no inconsistency can exist.
A single tool is too few for a server that might be expected to handle YouTube transcripts comprehensively. While it covers extraction, there are likely gaps such as searching transcripts, handling errors, or managing multiple videos, making the scope feel thin and incomplete.
The server is severely incomplete for a YouTube transcript domain. It only provides extraction, missing obvious operations like searching within transcripts, listing available transcripts, or handling transcript formats (e.g., timestamps, languages), which are common needs in this context.
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
An MCP server that gives any LLM or agent clean YouTube transcripts on demand: a single video, a whole channel, or a playlist, plus AI cleanup of auto-generated captions. API-key auth, credit-based, same backend as the public v1 API. Get a free API key with 25 free credits at youtubetranscriptdownload.com/account.
MCP server for RiverScript, an AI transcription platform - fetches transcripts shared via a link.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
Search YouTube, read video metadata, and fetch transcripts with language preferences
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/williamvd4/mcp-server-youtube-transcript'
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