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MalikElate

YouTube Transcript Extractor MCP

by MalikElate
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

YouTube 转录提取器 MCP 🎥

一个模型上下文协议 (MCP) 服务器，使 AI 助手能够从 YouTube 视频中提取文字记录。该工具专为与 Cursor 和 Claude Desktop 集成而设计，允许 AI 直接分析和处理 YouTube 视频内容。

特征

  • 🎯 从任何公开的 YouTube 视频中提取文字记录

  • 🔌 轻松与 Cursor 和 Claude Desktop 集成

  • 🚀 使用 TypeScript 构建以确保类型安全

  • 📦简单的设置和部署

  • 🛠️基于模型上下文协议

Related MCP server: YouTube Translate MCP

先决条件

  • Node.js（v16 或更高版本）

  • pnpm（推荐）或 npm

  • 用于提取转录内容的 YouTube 视频 URL

安装

  1. 克隆存储库：

git clone https://github.com/yourusername/yt-mcp.git
cd yt-mcp

  1. 安装依赖项：

pnpm install

  1. 构建项目：

pnpm run build

配置

对于光标

  1. 打开游标设置

  2. 导航至 MCP → 添加新的 MCP 服务器

  3. 使用以下设置进行配置：

    • 名称： youtube-transcript

    • 类型： command

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

对于克劳德桌面

将此配置添加到您的 Claude Desktop 配置中：

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

用法

配置完成后，AI 可以通过视频 URL 调用该工具，提取 YouTube 视频的文字记录。示例：

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

技术细节

该服务器使用以下方式构建：

限制

  • 仅适用于公开的 YouTube 视频

  • 视频必须启用字幕

  • 某些视频可能带有自动生成的字幕，但可能不是 100% 准确

故障排除

常见问题及解决方案：

  1. “无法找到视频 ID”错误

    • 确保 YouTube URL 完整且正确

    • 检查视频是否可以公开访问

  2. “没有可用的成绩单”错误

    • 验证视频是否已启用字幕

    • 尝试不同的视频以确认该工具是否正常工作

  3. 构建错误

    • 确保所有依赖项都已安装

    • 检查 Node.js 版本（应为 v16 或更高版本）

贡献

欢迎贡献代码！欢迎提交 Pull 请求。对于重大变更，请先提交一个 issue 来讨论您想要修改的内容。

执照

麻省理工学院

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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