mcp-server-youtube-transcript

mcp-server-youtube-transcript

Retrieve YouTube video transcripts via a Model Context Protocol server.

308
Stars
52
Forks
308
Watchers
9
Issues
This project implements a Model Context Protocol (MCP) server that provides seamless access to YouTube video transcripts and subtitles. Users can extract captions from videos using a simple and standardized interface, with support for multiple video URL formats and language-specific transcript retrieval. The server is designed for integration with tools such as Claude Desktop and includes robust error handling, security features, and automated deployment capabilities.

Key Features

Retrieves YouTube transcripts and subtitles
Supports multiple video URL formats and video IDs
Enables language-specific transcript retrieval
Provides detailed response metadata
Integrates seamlessly with Claude Desktop and Smithery
Robust error handling for invalid URLs and unavailable resources
Supports automated installation via CLI tools
Security features including parameter validation and timeouts
Development tools for testing and debugging (e.g., MCP Inspector)
MIT licensed for broad usage

Use Cases

Extracting subtitles from YouTube videos for content analysis
Integrating video transcript retrieval into productivity applications
Automating the generation of meeting notes from YouTube video content
Supporting accessibility workflows by providing text versions of video audio
Enhancing language learning tools with multi-language video transcripts
Developing AI assistants that require contextual data from media
Building chatbots capable of summarizing or referencing YouTube videos
Facilitating compliance and moderation via transcript search
Adding YouTube transcript retrieval to desktop AI clients
Sourcing structured video metadata for NLP pipelines

README

MseeP.ai Security Assessment Badge

YouTube Transcript Server

smithery badge

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:

bash
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 or video ID
      • lang (string, optional, default: "en"): Language code for transcript (e.g., 'ko', 'en')

Key Features

  • Support for multiple video URL formats
  • Language-specific transcript retrieval
  • Detailed metadata in responses

Configuration

To use with Claude Desktop, add this server configuration:

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

Install via tool

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

shell
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:

bash
npm install

Build the server:

bash
npm run build

For development with auto-rebuild:

bash
npm run watch

Testing

bash
npm test

Debugging

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

bash
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.

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

Star History

Star History Chart

Repository Owner

Repository Details

Language JavaScript
Default Branch main
Size 38 KB
Contributors 6
License MIT License
MCP Verified Sep 5, 2025

Programming Languages

JavaScript
82.41%
Dockerfile
8.9%
TypeScript
8.69%

Join Our Newsletter

Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.

We respect your privacy. Unsubscribe at any time.

Related MCPs

Discover similar Model Context Protocol servers

  • cloudflare/mcp-server-cloudflare

    cloudflare/mcp-server-cloudflare

    Connect Cloudflare services to Model Context Protocol (MCP) clients for AI-powered management.

    Cloudflare MCP Server enables integration between Cloudflare's suite of services and clients using the Model Context Protocol (MCP). It provides multiple specialized servers that allow AI models to access, analyze, and manage configurations, logs, analytics, and other features across Cloudflare's platform. Users can leverage natural language interfaces in compatible MCP clients to read data, gain insights, and perform automated actions on their Cloudflare accounts. This project aims to streamline the orchestration of security, development, monitoring, and infrastructure tasks through standardized MCP connections.

    • 2,919
    • MCP
    • cloudflare/mcp-server-cloudflare
  • k8s-mcp-server

    k8s-mcp-server

    Securely enable Claude to run Kubernetes CLI tools via Anthropic's Model Context Protocol.

    K8s MCP Server provides a Docker-based implementation of Anthropic's Model Context Protocol (MCP), allowing Claude to securely execute Kubernetes CLI tools such as kubectl, helm, istioctl, and argocd within a containerized environment. It integrates with Claude Desktop so users can interact with their Kubernetes clusters using natural language. The server emphasizes security by operating as a non-root user and offering strict command validation, while also supporting major cloud providers like AWS, Google Cloud, and Azure. Easy configuration and support for various Unix tools further enhance its capabilities.

    • 166
    • MCP
    • alexei-led/k8s-mcp-server
  • awslabs/mcp

    awslabs/mcp

    Specialized MCP servers for seamless AWS integration in AI and development environments.

    AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.

    • 6,220
    • MCP
    • awslabs/mcp
  • video-editing-mcp

    video-editing-mcp

    MCP server for uploading, editing, searching, and generating videos via Video Jungle and LLMs.

    Implements a Model Context Protocol (MCP) server for seamless video uploading, editing, searching, and generative editing workflows, powered by Video Jungle integration and LLM assistance. Provides a suite of tools for video asset management, automated video editing, and context-aware search leveraging multimedia analysis. Supports both cloud workflows through Video Jungle and local searching capabilities, such as accessing the Photos app database on MacOS. Designed for integration with clients like Claude Desktop and supports automation, debugging, and development through open protocols.

    • 207
    • MCP
    • burningion/video-editing-mcp
  • quran-mcp-server

    quran-mcp-server

    MCP server to access Quran.com API with AI tool compatibility.

    quran-mcp-server exposes the Quran.com corpus and associated data through a Model Context Protocol (MCP) server generated from an OpenAPI specification. It provides tool endpoints for chapters, verses, translations, tafsirs, audio, languages, and more. The server is designed for seamless integration with large language models (LLMs) and AI tools, supporting both Docker and Node.js environments. Advanced logging features and flexible deployment options are included for debugging and development.

    • 49
    • MCP
    • djalal/quran-mcp-server
  • mcp

    mcp

    Universal remote MCP server connecting AI clients to productivity tools.

    WayStation MCP acts as a remote Model Context Protocol (MCP) server, enabling seamless integration between AI clients like Claude or Cursor and a wide range of productivity applications, such as Notion, Monday, Airtable, Jira, and more. It supports multiple secure connection transports and offers both general and user-specific preauthenticated endpoints. The platform emphasizes ease of integration, OAuth2-based authentication, and broad app compatibility. Users can manage their integrations through a user dashboard, simplifying complex workflow automations for AI-powered productivity.

    • 27
    • MCP
    • waystation-ai/mcp
  • Didn't find tool you were looking for?

    Be as detailed as possible for better results