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kimtaeyoon83

mcp-server-youtube-transcript

by kimtaeyoon83

YouTube Transcript Server

Trust Score

A 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.

Installing via Smithery

To install YouTube Transcript Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @kimtaeyoon83/mcp-server-youtube-transcript --client claude

Components

Tools

  • get_transcript

    • Extract transcripts from YouTube videos

    • Inputs:

      • url (string, required): YouTube video URL, Shorts URL, or video ID

      • lang (string, optional, default: "en"): Language code for transcript (e.g., 'ko', 'en'). Automatically falls back to available languages if requested language is not found.

      • include_timestamps (boolean, optional, default: false): Include timestamps in output (e.g., '[0:05] text')

      • strip_ads (boolean, optional, default: true): Filter out sponsorships, ads, and promotional content from transcript based on chapter markers

  • analyze_video (optional, requires a TwelveLabs API key)

    • Analyze a video with TwelveLabs Pegasus, a video-understanding model. Unlike get_transcript, this reasons over what is shown on screen, so it produces useful summaries and answers even for videos with little or no speech (demos, gameplay, b-roll, music videos).

    • Inputs:

      • url (string, required): A publicly reachable direct video URL (e.g. an .mp4/.mov/.webm link or a pre-signed URL). TwelveLabs fetches the file server-side, so a YouTube watch page URL will not work — it serves HTML, not a raw video stream.

      • prompt (string, optional): Instruction or question for the model (e.g. "Summarize this video in 3 sentences" or "What products are shown?"). Defaults to a general summary.

      • model (string, optional, default: "pegasus1.2"): Pegasus model to use ("pegasus1.2" or "pegasus1.5").

      • max_tokens (number, optional, default: 2048): Maximum response length in tokens.

    • Requires the TWELVELABS_API_KEY environment variable. The transcript tool works without it; analysis is fully opt-in. Grab a free key at twelvelabs.io — there's a generous free tier.

Related MCP server: YouTube Transcript Extractor MCP

Key Features

  • Support for multiple video URL formats (including YouTube Shorts)

  • Language-specific transcript retrieval with automatic fallback

  • Optional timestamps for referencing specific moments

  • Built-in ad/sponsorship filtering (enabled by default)

  • Zero external dependencies for transcript fetching

  • Detailed metadata in responses

Configuration

To use with Claude Desktop, add this server configuration:

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "npx",
      "args": ["-y", "@kimtaeyoon83/mcp-server-youtube-transcript"]
    }
  }
}

To enable the optional analyze_video tool, add your TwelveLabs API key:

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "npx",
      "args": ["-y", "@kimtaeyoon83/mcp-server-youtube-transcript"],
      "env": {
        "TWELVELABS_API_KEY": "your-twelvelabs-api-key"
      }
    }
  }
}

Install via tool

mcp-get A command-line tool for installing and managing Model Context Protocol (MCP) servers.

npx @michaellatman/mcp-get@latest install @kimtaeyoon83/mcp-server-youtube-transcript

Awesome-mcp-servers

awesome-mcp-servers A curated list of awesome Model Context Protocol (MCP) servers.

Development

Prerequisites

  • Node.js 18 or higher

  • npm or yarn

Setup

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Testing

npm test

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector for development:

npm run inspector

Running evals

The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.

OPENAI_API_KEY=your-key  npx mcp-eval src/evals/evals.ts src/index.ts

Error Handling

The server implements robust error handling for common scenarios:

  • Invalid video URLs or IDs

  • Unavailable transcripts

  • Language availability issues

  • Network errors

Usage Examples

  1. Get transcript by video URL:

await server.callTool("get_transcript", {
  url: "https://www.youtube.com/watch?v=VIDEO_ID",
  lang: "en"
});
  1. Get transcript by video ID:

await server.callTool("get_transcript", {
  url: "VIDEO_ID",
  lang: "ko"
});
  1. Get transcript from YouTube Shorts:

await server.callTool("get_transcript", {
  url: "https://www.youtube.com/shorts/VIDEO_ID"
});
  1. Get transcript with timestamps:

await server.callTool("get_transcript", {
  url: "VIDEO_ID",
  include_timestamps: true
});
  1. Get raw transcript without ad filtering:

await server.callTool("get_transcript", {
  url: "VIDEO_ID",
  strip_ads: false
});
  1. How to Extract YouTube Subtitles in Claude Desktop App

chat: https://youtu.be/ODaHJzOyVCQ?si=aXkJgso96Deri0aB Extract subtitles

Security Considerations

The server:

  • Validates all input parameters

  • Handles YouTube API errors gracefully

  • Implements timeouts for transcript retrieval

  • Provides detailed error messages for troubleshooting

License

This MCP server is licensed under the MIT License. See the LICENSE file for details.

Available Tools

1 tool
get_transcriptA
Read-only

Extract transcript from a YouTube video URL or ID. Automatically falls back to available languages if requested language is not available.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL or ID
langNoLanguage code for transcript (e.g., 'ko', 'en'). Will fall back to available language if not found.en
include_timestampsNoInclude timestamps in output (e.g., '[0:05] text'). Useful for referencing specific moments. Default: false
strip_adsNoFilter out sponsored segments from transcript based on chapter markers (e.g., chapters marked as 'Werbung', 'Ad', 'Sponsor'). Default: true

Output Schema

ParametersJSON Schema
NameRequiredDescription
metaNoTitle | Author | Subs | Views | Date
contentYes

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only and open-world hints, but the description adds valuable behavioral context: the automatic language fallback mechanism and the ad-stripping functionality based on chapter markers. This goes beyond annotations by explaining conditional behaviors and processing logic, though it doesn't cover rate limits or error handling.

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, well-structured sentence that efficiently conveys the core functionality and key behavioral traits (language fallback). Every word serves a purpose, with no redundancy or unnecessary elaboration, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (4 parameters, read-only operation) and the presence of both rich annotations and an output schema, the description is largely complete. It covers the main action and notable behaviors, though it could benefit from mentioning output format or error cases. The output schema likely handles return values, reducing the burden on the description.

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?

With 100% schema description coverage, the input schema fully documents all parameters. The description mentions language fallback and ad-stripping, which are already covered in the schema descriptions for 'lang' and 'strip_ads'. It adds no significant semantic information beyond what the schema provides, so 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.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Extract transcript'), resource ('from a YouTube video'), and input type ('URL or ID'). It also mentions the fallback behavior for language selection, which adds specificity. With no sibling tools to distinguish from, this is maximally clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for extracting transcripts from YouTube videos, but provides no explicit guidance on when to use this tool versus alternatives (e.g., other transcript tools or manual methods). Since there are no sibling tools, it doesn't need to differentiate, but it lacks broader context about prerequisites or typical use cases.

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 updatev1.0.0
    • Addedget_transcript

TDQS

A3.9/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool's purpose is clearly defined and distinct by default.

Naming Consistency5/5

A single tool inherently has consistent naming, as there are no other tools to compare it against. The name 'get_transcript' follows a clear verb_noun pattern.

Tool Count2/5

One tool is too few for a server named 'youtube-transcript', which suggests a broader domain. A complete surface might include tools for searching videos, listing transcripts, or handling metadata, making this feel thin and incomplete.

Completeness2/5

The server's purpose implies transcript-related operations, but with only a 'get' tool, there are significant gaps. For example, no tools for listing available transcripts, searching within transcripts, or managing transcript data, which limits agent workflows.

Maintenance

ActivityStale
ResponsivenessSyncing

Resources

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