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MalikElate

YouTube Transcript Extractor MCP

by MalikElate
OverviewSchemaRelated ServersScoreDiscussions
TypeScript

YouTube Transcript Extractor MCP 🎥

A Model Context Protocol (MCP) server that enables AI assistants to extract transcripts from YouTube videos. Built for integration with Cursor and Claude Desktop, this tool allows AI to analyze and work with YouTube video content directly.

Features

  • 🎯 Extract transcripts from any public YouTube video

  • 🔌 Easy integration with Cursor and Claude Desktop

  • 🚀 Built with TypeScript for type safety

  • 📦 Simple setup and deployment

  • 🛠️ Based on the Model Context Protocol

Related MCP server: YouTube Translate MCP

Prerequisites

  • Node.js (v16 or higher)

  • pnpm (recommended) or npm

  • A YouTube video URL to extract transcripts from

Installation

  1. Clone the repository:

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

  1. Install dependencies:

pnpm install

  1. Build the project:

pnpm run build

Configuration

For Cursor

  1. Open Cursor Settings

  2. Navigate to MCP → Add new MCP server

  3. Configure with these settings:

    • Name: youtube-transcript

    • Type: command

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

For Claude Desktop

Add this configuration to your Claude Desktop config:

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

Usage

Once configured, the AI can extract transcripts from YouTube videos by calling the tool with a video URL. Example:

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

Technical Details

The server is built using:

Limitations

  • Only works with public YouTube videos

  • Videos must have captions/subtitles enabled

  • Some videos may have auto-generated captions which might not be 100% accurate

Troubleshooting

Common issues and solutions:

  1. "Cannot find video ID" error

    • Ensure the YouTube URL is complete and correct

    • Check if the video is publicly accessible

  2. "No transcript available" error

    • Verify that the video has captions enabled

    • Try a different video to confirm the tool is working

  3. Build errors

    • Make sure all dependencies are installed

    • Check Node.js version (should be v16 or higher)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

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. Dates show when Glama detected each change.

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

B3.1/5.0
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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