YouTube Transcript MCP Server
YouTube 成绩单 MCP 服务器
该 MCP 服务器检索给定 YouTube 视频 URL 的成绩单。
工具
该 MCP 服务器提供以下工具:
get_transcript
获取指定 YouTube 视频的成绩单。
参数
url (字符串) :YouTube 视频的完整 URL。此字段为必填项。
lang (字符串,可选) :转录所需的语言。如未指定,则默认为
en。
Related MCP server: YouTube Transcript Server
安装
对于 Goose CLI
要在 Goose CLI 中启用 YouTube Transcript 扩展,请编辑配置文件~/.config/goose/config.yaml以包含以下条目:
extensions:
youtube-transcript:
name: Youtube Transcript
cmd: uvx
args: [--from, git+https://github.com/jkawamoto/mcp-youtube-transcript, mcp-youtube-transcript]
enabled: true
type: stdio适用于 Goose Desktop
使用以下设置添加新扩展:
类型:标准IO
ID :youtube-transcript
名称:Youtube 成绩单
描述:检索 YouTube 视频的成绩单
命令:
uvx --from git+https://github.com/jkawamoto/mcp-youtube-transcript mcp-youtube-transcript
有关在 Goose Desktop 中配置 MCP 服务器的更多详细信息,请参阅文档:使用扩展 - MCP 服务器。
对于克劳德桌面
要为 Claude Desktop 配置此服务器,请在mcpServers下使用以下条目编辑claude_desktop_config.json文件:
{
"mcpServers": {
"youtube-transcript": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/jkawamoto/mcp-youtube-transcript",
"mcp-youtube-transcript"
]
}
}
}编辑完成后,重新启动应用程序。更多信息,请参阅:针对 Claude 桌面用户 - 模型上下文协议。
通过 Smithery 安装
要通过Smithery自动安装 Claude Desktop 的 Youtube Transcript:
npx -y @smithery/cli install @jkawamoto/mcp-youtube-transcript --client claude使用代理服务器
在限制访问 YouTube 的环境中,您可以使用代理服务器。
使用Webshare时,使用环境变量WEBSHARE_PROXY_USERNAME和WEBSHARE_PROXY_PASSWORD或命令行参数--webshare-proxy-username和--webshare-proxy-password设置住宅代理的用户名和密码。
使用其他代理服务器时,使用环境变量HTTP_PROXY或HTTPS_PROXY或者命令行参数--http-proxy或--https-proxy设置代理服务器 URL。
有关更多详细信息,请访问: 解决 IP 禁令 - YouTube 成绩单 API 。
执照
此应用程序采用 MIT 许可证。有关更多详细信息,请参阅许可证文件。
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
Resources
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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.
Related MCP Servers
- 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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