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YouTube Transcript MCP Server

YouTube Transcript MCP Server

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github.com/jkawamotoMedia & Design494Updated today

About YouTube Transcript MCP Server

YouTube Transcript MCP Server fetches transcripts and metadata for video-based LLM workflows. It supports timestamped segments, language discovery, pagination for long transcripts, and proxy configuration.

Key features

  1. 01Plain-text and timestamped transcripts
  2. 02Video metadata retrieval
  3. 03Available transcript language listing
  4. 04Chunking and pagination for long videos
  5. 05Residential and HTTP/HTTPS proxy support

Use cases

  1. 01Retrieve transcripts from lectures and podcasts
  2. 02Page through long video transcripts
  3. 03Select an available transcript language
  4. 04Fetch video title and channel information

MCP support

The MCP server exposes tools for retrieving plain-text or timed transcripts, listing available languages, and fetching video metadata. MCP clients can request long transcripts in chunks using a cursor.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository
Packages
mcpbmcp-youtube-transcript.mcpb0.8.3

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

YouTube Transcript MCP Server

uv Python Application pre-commit GitHub License Dockerhub

A Model Context Protocol (MCP) server that fetches transcripts and metadata from YouTube videos directly into your LLM workflows.

Designed specifically for AI agents, it seamlessly handles long-form videos through automatic pagination and provides robust proxy support to circumvent YouTube rate limits and IP bans.

Key Features

  • Rich Transcript Retrieval: Fetch raw text, timestamped segments, and video metadata in multiple languages.
  • Smart Chunking & Pagination: Automatically chunks long transcripts (default: 50,000 characters) to prevent context window overflow, letting models page through hours of video effortlessly.
  • Resilient Proxy Support: Built-in support for residential proxies (Webshare, ScrapingAnt) and standard HTTP/HTTPS proxies to prevent IP blocks.
  • Universal Compatibility: Works with Claude Desktop, Cursor, LM Studio, Goose, and any standard MCP client.

Quick Start & Installation

Note

You'll need uv installed on your system to use uvx command.

This server communicates via standard stdio. Most MCP clients can run it directly using uvx (part of Astral uv).

General Configuration (Standard MCP JSON)

Add this entry to your client's MCP configuration file (typically under mcpServers):

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/jkawamoto/mcp-youtube-transcript",
        "mcp-youtube-transcript"
      ]
    }
  }
}
Client-Specific Setup Guides (Click to expand)
Claude Desktop
  • GUI (Drag & Drop): Download the .mcpb bundle from the Releases page and drop it into your Claude Desktop Settings.
  • Manual Config: Add the JSON above to claude_desktop_config.json (restart Claude Desktop after saving):
    • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
    • Windows: %APPDATA%\Claude\claude_desktop_config.json
Cursor
  1. Go to Cursor Settings > Features > MCP Servers.
  2. Click + Add New MCP Server.
  3. Name: youtube-transcript, Type: command.
  4. Command: uvx --from git+https://github.com/jkawamoto/mcp-youtube-transcript mcp-youtube-transcript
Goose

Please refer to this tutorial for detailed installation instructions: YouTube Transcript Extension.

LM Studio

To configure this server for LM Studio, click the button below.

Add MCP Server youtube-transcript to LM Studio

Using Docker

A Docker image for this server is available on Docker Hub. Please refer to the Docker Hub page for detailed usage instructions and documentation.

Available Tools

The server registers the following MCP tools for LLM agents:

ToolDescription
get_transcriptRetrieves the plain-text transcript for a YouTube video URL.
get_timed_transcriptRetrieves transcript segments with start times and durations.
get_available_languagesLists all available transcript languages (manual & auto-generated).
get_video_infoFetches video metadata such as title and channel information.
Tool Parameters & Schema
  • get_transcript

    • url (string, required): Full YouTube video URL.
    • lang (string, optional): Preferred language code (defaults to "en").
    • next_cursor (integer, optional): Cursor to fetch the next chunk for long videos.
  • get_timed_transcript

    • url (string, required): Full YouTube video URL.
    • lang (string, optional): Preferred language code (defaults to "en").
    • next_cursor (integer, optional): Cursor to fetch the next chunk.
  • get_available_languages

    • url (string, required): Full YouTube video URL.
  • get_video_info

    • url (string, required): Full YouTube video URL.

Advanced Configuration

Handling Long Videos (Pagination)

Long videos (e.g., lectures, conferences, podcast episodes) can quickly exceed LLM token context limits. By default, transcripts exceeding 50,000 characters are chunked. When a response is split, a next_cursor is provided so the LLM agent can autonomously query the rest.

To customize the chunk character limit, supply --response-limit. To disable pagination and fetch the entire transcript at once, set --response-limit to a negative value (e.g., -1):

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/jkawamoto/mcp-youtube-transcript",
        "mcp-youtube-transcript",
        "--response-limit",
        "15000"
      ]
    }
  }
}
Avoiding IP Bans (Proxy Setup)

YouTube aggressively blocks automated transcript requests from cloud providers and data center IPs. Using residential or rotating proxies ensures uninterrupted access.

1. Webshare Residential Proxy

Set credentials via environment variables or command-line flags:

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/jkawamoto/mcp-youtube-transcript",
        "mcp-youtube-transcript"
      ],
      "env": {
        "WEBSHARE_PROXY_USERNAME": "your_username",
        "WEBSHARE_PROXY_PASSWORD": "your_password"
      }
    }
  }
}

(CLI equivalents: --webshare-proxy-username and --webshare-proxy-password)

2. ScrapingAnt

If using ScrapingAnt, supply your API token:

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/jkawamoto/mcp-youtube-transcript",
        "mcp-youtube-transcript"
      ],
      "env": {
        "SCRAPINGANT_API_TOKEN": "your_api_token"
      }
    }
  }
}

(CLI equivalent: --scrapingant-api-token)

Accessing YouTube requires a paid ScrapingAnt Web Scraping API subscription. YouTube access requires residential proxies, which consume more ScrapingAnt credits than standard proxy requests. See the ScrapingAnt credit cost documentation for details.

3. Standard / Generic HTTP & HTTPS Proxies

Specify custom proxy endpoints via HTTP_PROXY / HTTPS_PROXY (or --http-proxy / --https-proxy):

{
  "mcpServers": {
    "youtube-transcript": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/jkawamoto/mcp-youtube-transcript",
        "mcp-youtube-transcript"
      ],
      "env": {
        "HTTPS_PROXY": "http://username:[email protected]:8080"
      }
    }
  }
}

For more details, please visit: Working around IP bans - YouTube Transcript API.

License

This application is licensed under the MIT License. See the LICENSE file for more details.

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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.