What can you do with this server?

Fetch YouTube transcripts, timed transcripts, video metadata, and available languages for LLM workflows. * Retrieve a video's plain-text transcript, optionally in a preferred language and paginated with next_cursor. * Retrieve a timed transcript as snippets with text, start time, and duration, also paginated. * Fetch video metadata including title, description, uploader, upload date, and duration. * List available transcript languages, including manual and auto-generated options. * Support long videos through automatic chunking/pagination and proxy configuration to avoid YouTube IP bans.

Which integrations are available for this server?

Retrieves transcripts from YouTube videos, allowing users to fetch transcripts in different languages from specified YouTube video URLs

How do I use YouTube Transcript MCP Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@YouTube Transcript MCP Server get transcript for https://youtu.be/dQw4w9WgXcQ" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

de en es ja ko ru zh

YouTube Transcript MCP Server

by jkawamoto

Overview Schema Source Related Servers Discussions Admin

Python

Remote

YouTube Transcript MCP Server

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.

Related MCP server: YouTube Transcript Server

Quick Start & Installation

NOTE

You'll needuv 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"
      ]
    }
  }
}

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

Go to Cursor Settings > Features > MCP Servers.
Click + Add New MCP Server.
Name: youtube-transcript, Type: command.
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:

Tool	Description
`get_transcript`	Retrieves the plain-text transcript for a YouTube video URL.
`get_timed_transcript`	Retrieves transcript segments with start times and durations.
`get_available_languages`	Lists all available transcript languages (manual & auto-generated).
`get_video_info`	Fetches video metadata such as title and channel information.

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:password@proxy.example.com: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.

Available Tools

4 tools

get_available_languagesA

Retrieves the available languages for the video.

Name	Required	Description	Default
`url`	Yes	The URL of the YouTube video

Output Schema

Name	Required	Description
`result`	Yes

TDQS

A3.6/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It correctly implies a read-only operation, but does not explicitly state that it is non-destructive, has no side effects, or any rate limits. The minimal description is adequate but lacks depth.

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, concise sentence with no unnecessary words. It front-loads the purpose and is appropriately sized for a simple retrieval tool.

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 that an output schema exists (documenting return values), the description is largely sufficient. However, it could briefly mention that the result is typically used to select a language for transcript retrieval, linking it to sibling tools. Otherwise, it is complete for a straightforward tool.

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?

Schema coverage is 100%, so the schema already documents the 'url' parameter. The description adds no additional semantics beyond what the schema provides, merely repeating that it is for a video. This meets the baseline expectation of high schema coverage.

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 action ('retrieves') and the resource ('available languages for the video'). It effectively distinguishes from sibling tools like get_timed_transcript and get_transcript, which deal with transcript content rather than language options.

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. There is no mention of prerequisites, such as needing to call this before selecting a language for transcripts, or any comparison with sibling tools. This leaves an AI agent without context for decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_timed_transcriptB

Retrieves the transcript of a YouTube video with timestamps.

Name	Required	Description	Default
`url`	Yes	The URL of the YouTube video
`lang`	No	The preferred language for the transcript	en
`next_cursor`	No	Cursor to retrieve the next page of the transcript

Output Schema

Name	Required	Description
`title`	Yes	Title of the video
`snippets`	Yes	Transcript snippets of the video
`next_cursor`	No	Cursor to retrieve the next page of the transcript

TDQS

B3.3/5.0

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 behavioral disclosure burden. It states the basic retrieval behavior but does not mention pagination behavior despite the next_cursor parameter, language fallback behavior, error cases, or rate limits.

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 front-loaded sentence with no wasted words. It immediately communicates the core capability.

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

Completeness3/5

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

The tool has an output schema and full parameter descriptions, which reduces the description's burden. However, the description does not address pagination, language preference behavior, or sibling differentiation, leaving some contextual gaps.

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?

Schema description coverage is 100%, so the schema already documents url, lang, and next_cursor. The description adds no parameter meaning beyond the schema, which is acceptable but not additive.

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 states a specific verb and resource: retrieves the transcript of a YouTube video, with timestamps. This is clear, but it does not explicitly distinguish itself from the sibling get_transcript beyond the implied timestamp feature.

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 phrase 'with timestamps' implies when this tool is preferable, but the description gives no explicit guidance about when to use it instead of get_transcript or how it relates to get_available_languages.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_transcriptC

Retrieves the transcript of a YouTube video.

Name	Required	Description	Default
`url`	Yes	The URL of the YouTube video
`lang`	No	The preferred language for the transcript	en
`next_cursor`	No	Cursor to retrieve the next page of the transcript

Output Schema

Name	Required	Description
`title`	Yes	Title of the video
`transcript`	Yes	Transcript of the video
`next_cursor`	No	Cursor to retrieve the next page of the transcript

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 behavioral burden. It does not mention pagination behavior despite the next_cursor parameter, language fallback behavior, authentication requirements, 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no wasted words. It is efficient, though its terseness leaves important usage and behavioral context absent.

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

Completeness3/5

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

The tool is simple and has a rich input schema plus an output schema, so the minimal description is partly sufficient. However, it omits sibling differentiation and behavioral details such as pagination, leaving clear gaps for an agent selecting among transcript-related tools.

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?

Schema description coverage is 100%, so the schema already documents url, lang, and next_cursor. The description adds no parameter meaning beyond the schema, which matches the baseline of 3 when structured fields do the heavy lifting.

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 states a specific verb and resource: retrieving a YouTube video transcript. It is clear what the tool does, but it does not distinguish itself from the sibling tool get_timed_transcript, which likely returns a timed variant.

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 gives no guidance on when to use this tool versus alternatives such as get_timed_transcript or get_available_languages. It only restates the action, leaving the agent to infer the selection context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_video_infoC

Retrieves the video information.

Name	Required	Description	Default
`url`	Yes	The URL of the YouTube video

Output Schema

Name	Required	Description
`title`	Yes	Title of the video
`duration`	Yes	Duration of the video
`uploader`	Yes	Uploader of the video
`description`	Yes	Description of the video
`upload_date`	Yes	Upload date of the video

TDQS

C2.9/5.0

Behavior2/5

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

No annotations provided, so the description must disclose behavioral traits. It only says 'retrieves' without confirming read-only nature, side effects, or any constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is minimal but does not provide enough detail to be useful; it sacrifices informativeness for brevity.

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

Completeness3/5

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

Given the presence of an output schema (not shown) and sibling tools, the description is adequate but could specify the scope of 'video information' and how it relates to the transcript-focused siblings.

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?

Schema description coverage is 100% for the sole parameter 'url', and the description adds no extra meaning beyond what the schema already provides.

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 action (retrieves) and resource (video information), but it does not specify what type of information (e.g., metadata, statistics) nor differentiate from sibling tools focused on transcripts.

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?

No guidance on when to use this tool versus siblings like get_transcript or get_available_languages. No context on prerequisites or alternatives.

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.

2 tool updatesv0.8.3Oct 30, 2026

Changedget_timed_transcript2 fields changed

changedInput schema / properties / next_cursor / anyOf

Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]

changedOutput schema / properties / next_cursor / anyOf

Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]

Changedget_transcript2 fields changed

changedInput schema / properties / next_cursor / anyOf

Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]

changedOutput schema / properties / next_cursor / anyOf

Previous value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "type": "integer"
+  },
+  {
+    "type": "null"
+  }
+]

1 tool updatev0.6.2May 6, 2026
- Addedget_available_languages
2 tool updatesv1.0.0Jan 2, 2026
- Addedget_timed_transcript
- Addedget_video_info
1 tool updateAug 18, 2025
- First observedget_transcript

Deploy Server

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TDQS

A3.5/5.0

Scored 2026-10-30 16:00 across 4 tools

Disambiguation4/5

Each tool targets a distinct output type, though get_transcript and get_timed_transcript overlap heavily in purpose and are only separated by the presence of timestamps. get_available_languages and get_video_info are clearly distinct from transcript retrieval.

Naming Consistency5/5

All four tools follow a consistent get_noun snake_case pattern, making the set highly predictable and readable.

Tool Count5/5

Four tightly scoped tools is appropriate for a focused YouTube transcript server. Each tool earns its place without extraneous surface area.

Completeness4/5

Core needs—transcript text, timestamped transcript, language availability, and video metadata—are covered. Minor gaps like transcript translation or search within a transcript are not present but are not essential to the stated purpose.

Maintenance

ActivityActive

ResponsivenessSlow

Resources

Related MCP Connectors

YouTube Transcripts
io.github.projectworks007
Transcripts of YouTube videos, playlists and channels with timestamps; SRT or WebVTT too.
Entertainment & Media Multimedia Processing Web Scraping
1
https://mcp.apify.com/?tools=highbrow_fame/youtube-transcript-fast,highbrow_fame/youtube-channel-api,highbrow_fame/youtube-video-details-api
YouTube Translate
io.github.brianshin22
Transcripts, translations, summaries, subtitles, and search for public YouTube videos.
Language Translation Text Summarization Search
15
https://api.youtubetranslate.com/mcp
YouTube Transcripts, Search & Summaries
io.github.gunnargray-dev
YouTube transcripts, video search, chapters and extractive summaries. No YouTube API key, no LLM.
Entertainment & Media Text Summarization Search
1
https://parallelstudio--youtube-transcripts-mcp.apify.actor/mcp
Wicked YouTube Transcript API — Captions, Timestamps, SRT & VTT
io.github.myworkingmemory
YouTube transcript API: batch video captions, timestamps, metadata and SRT/VTT subtitles.
Entertainment & Media Multimedia Processing
1
https://mcp.apify.com/?tools=myworkingmemory/wicked-youtube-transcript-scraper-api

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Key Features

Quick Start & Installation

General Configuration (Standard MCP JSON)

Claude Desktop

Cursor

Using Docker

Available Tools

Advanced Configuration

Handling Long Videos (Pagination)

Avoiding IP Bans (Proxy Setup)

1. Webshare Residential Proxy

2. ScrapingAnt

3. Standard / Generic HTTP & HTTPS Proxies

License

Available Tools

Output Schema

Output Schema

Output Schema

Output Schema

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

Appeared in Searches