YouTube Transcript MCP Server
YouTube 대본 MCP 서버
이 MCP 서버는 주어진 YouTube 비디오 URL에 대한 대본을 검색합니다.
도구
이 MCP 서버는 다음과 같은 도구를 제공합니다.
get_transcript
지정된 YouTube 비디오의 대본을 가져옵니다.
매개변수
url (문자열) : YouTube 동영상의 전체 URL입니다. 이 필드는 필수입니다.
lang (문자열, 선택 사항) : 스크립트에 사용할 언어입니다. 지정하지 않으면 기본값은
en입니다.
Related MCP server: YouTube Transcript Server
설치
Goose CLI의 경우
Goose CLI에서 YouTube 대본 확장 기능을 활성화하려면 구성 파일 ~/.config/goose/config.yaml 편집하여 다음 항목을 포함하세요.
지엑스피1
Goose Desktop용
다음 설정으로 새로운 확장 프로그램을 추가합니다.
유형 : 표준 IO
ID : youtube-transcript
이름 : 유튜브 대본
설명 : YouTube 동영상의 대본을 검색합니다.
명령어 :
uvx --from git+https://github.com/jkawamoto/mcp-youtube-transcript mcp-youtube-transcript
Goose Desktop에서 MCP 서버를 구성하는 방법에 대한 자세한 내용은 다음 설명서를 참조하세요: 확장 기능 사용 - MCP 서버 .
클로드 데스크탑용
Claude Desktop에 맞게 이 서버를 구성하려면 mcpServers 아래에 다음 항목을 추가하여 claude_desktop_config.json 파일을 편집합니다.
{
"mcpServers": {
"youtube-transcript": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/jkawamoto/mcp-youtube-transcript",
"mcp-youtube-transcript"
]
}
}
}편집 후 애플리케이션을 다시 시작하세요. 자세한 내용은 Claude Desktop 사용자용 - 모델 컨텍스트 프로토콜을 참조하세요.
Smithery를 통해 설치
Smithery를 통해 Claude Desktop용 Youtube 대본을 자동으로 설치하는 방법:
npx -y @smithery/cli install @jkawamoto/mcp-youtube-transcript --client claude프록시 서버 사용
YouTube 접속이 제한된 환경에서는 프록시 서버를 사용할 수 있습니다.
Webshare를 사용할 때 환경 변수 WEBSHARE_PROXY_USERNAME 및 WEBSHARE_PROXY_PASSWORD 또는 명령줄 인수 --webshare-proxy-username 및 --webshare-proxy-password 사용하여 Residential Proxy의 사용자 이름과 비밀번호를 설정합니다.
다른 프록시 서버를 사용하는 경우 환경 변수 HTTP_PROXY 또는 HTTPS_PROXY 또는 명령줄 인수 --http-proxy 또는 --https-proxy 사용하여 프록시 서버 URL을 설정합니다.
자세한 내용은 IP 차단 해결 - YouTube 대본 API를 참조하세요.
특허
이 애플리케이션은 MIT 라이선스에 따라 라이선스가 부여됩니다. 자세한 내용은 라이선스 파일을 참조하세요.
Available Tools
4 toolsget_available_languagesA
Retrieves the available languages for the video.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL of the YouTube video |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It correctly implies a read-only operation, but does not explicitly state that it is non-destructive, has no side effects, or any rate limits. The minimal description is adequate but lacks depth.
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, concise sentence with no unnecessary words. It front-loads the purpose and is appropriately sized for a simple retrieval tool.
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 that an output schema exists (documenting return values), the description is largely sufficient. However, it could briefly mention that the result is typically used to select a language for transcript retrieval, linking it to sibling tools. Otherwise, it is complete for a straightforward tool.
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?
Schema coverage is 100%, so the schema already documents the 'url' parameter. The description adds no additional semantics beyond what the schema provides, merely repeating that it is for a video. This meets the baseline expectation of 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 action ('retrieves') and the resource ('available languages for the video'). It effectively distinguishes from sibling tools like get_timed_transcript and get_transcript, which deal with transcript content rather than language options.
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. There is no mention of prerequisites, such as needing to call this before selecting a language for transcripts, or any comparison with sibling tools. This leaves an AI agent without context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_timed_transcriptA
Retrieves the transcript of a YouTube video with timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL of the YouTube video | |
| lang | No | The preferred language for the transcript | en |
| next_cursor | No | Cursor to retrieve the next page of the transcript |
Output Schema
| Name | Required | Description |
|---|---|---|
| title | Yes | Title of the video |
| snippets | Yes | Transcript snippets of the video |
| next_cursor | No | Cursor to retrieve the next page of the transcript |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description does not disclose behavioral traits such as pagination (despite the next_cursor parameter), rate limits, or authentication requirements. The basic retrieval purpose is clear, but critical context for the agent is missing.
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?
A single 7-word sentence that is perfectly concise and front-loaded with the essential action and distinguishing feature.
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 presence of an output schema, the description is minimally adequate. However, it lacks context about pagination, language fallback, and error handling, which are relevant for a tool with three parameters and a cursor.
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?
Schema description coverage is 100%, and the description adds no extra meaning beyond what the schema already provides for each parameter. Baseline score of 3 applies.
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 'retrieves' and resource 'transcript of a YouTube video with timestamps', distinguishing it from the sibling 'get_transcript' which presumably lacks timestamps.
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?
No explicit guidance on when to use this tool versus alternatives like 'get_transcript' or 'get_available_languages'. Purpose clarity provides implicit distinction but no direct recommendation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_transcriptC
Retrieves the transcript of a YouTube video.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL of the YouTube video | |
| lang | No | The preferred language for the transcript | en |
| next_cursor | No | Cursor to retrieve the next page of the transcript |
Output Schema
| Name | Required | Description |
|---|---|---|
| title | Yes | Title of the video |
| transcript | Yes | Transcript of the video |
| next_cursor | No | Cursor to retrieve the next page of the transcript |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description should carry the burden. It says 'retrieves' but does not disclose pagination (next_cursor parameter), language handling default, or output format. The schema hints at pagination, but the description omits this behavioral trait.
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 sentence, very concise and to the point. However, it may be too terse given the complexity (pagination, language option). Still, it earns its place with no filler.
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 that an output schema exists (mentioned in context signals) and input schema covers all parameters, the description covers the core purpose. However, it lacks details on pagination behavior, language fallback, and comparison with siblings, leaving some gaps for a complete understanding.
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?
Schema description coverage is 100%, and the descriptions for url, lang, and next_cursor are already informative. The tool description adds no additional semantic value beyond what the schema provides, so baseline 3 is appropriate.
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 tool retrieves a YouTube video transcript, but lacks differentiation from sibling tools like get_timed_transcript or get_available_languages. The verb 'retrieves' and resource 'transcript' are specific, but without context on what format (plain vs timed) or scope, it's not fully distinguished.
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?
No guidance is provided on when to use this tool versus siblings. For example, get_timed_transcript might return timestamps, while this one might return plain text. The agent has no criteria to choose among them.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_video_infoC
Retrieves the video information.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The URL of the YouTube video |
Output Schema
| Name | Required | Description |
|---|---|---|
| title | Yes | Title of the video |
| duration | Yes | Duration of the video |
| uploader | Yes | Uploader of the video |
| description | Yes | Description of the video |
| upload_date | Yes | Upload date of the video |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavioral traits. It only says 'retrieves' without confirming read-only nature, side effects, or any constraints.
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 short sentence, which is minimal but does not provide enough detail to be useful; it sacrifices informativeness for brevity.
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 presence of an output schema (not shown) and sibling tools, the description is adequate but could specify the scope of 'video information' and how it relates to the transcript-focused siblings.
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?
Schema description coverage is 100% for the sole parameter 'url', and the description adds no extra meaning beyond what the schema already provides.
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 action (retrieves) and resource (video information), but it does not specify what type of information (e.g., metadata, statistics) nor differentiate from sibling tools focused on transcripts.
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?
No guidance on when to use this tool versus siblings like get_transcript or get_available_languages. No context on prerequisites or alternatives.
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
v0.6.2- Added
get_available_languages
2 tool updates
v1.0.0- Added
get_timed_transcript - Added
get_video_info
1 tool update
- First observed
get_transcript
TDQS
Most tools are distinct: get_available_languages and get_video_info have clear purposes. get_transcript and get_timed_transcript overlap but differ by timestamps, creating slight ambiguity.
All tools follow a consistent 'get_' prefix with descriptive nouns in snake_case, making the pattern predictable.
Four tools cover core operations (transcript, timed transcript, languages, video info) without excess or deficiency for a transcript-focused server.
The tool set covers essential transcript retrieval and video information. Missing features like search or playlist support are outside the stated domain, so completeness is high but not maximal.
Maintenance
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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.
Fetch transcripts, subtitles, chapters, metadata and frames from YouTube and 10+ video platforms
Fetch the full transcript of any YouTube video as clean text. No API key, no signup.
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- AlicenseAqualityDmaintenanceA Model Context Protocol server that enables retrieval of transcripts from YouTube videos. This server provides direct access to video captions and subtitles through a simple interface.1797590MIT
- AlicenseBqualityDmaintenanceA Model Context Protocol server that enables retrieval of transcripts from YouTube videos with language-specific support.17971MIT
- AlicenseAqualityDmaintenanceA Model Context Protocol server that enables retrieval of transcripts from YouTube videos. This server provides direct access to video transcripts and subtitles through a simple interface, making it ideal for content analysis and processing.146236MIT
- AlicenseBqualityDmaintenanceAn MCP server designed to fetch transcripts for YouTube videos. It enables AI tools to access video text content for tasks like summarization, analysis, and key takeaway extraction.173MIT
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