mcp-youtube-transcript
The MCP YouTube Transcript Server allows you to extract and process transcripts from YouTube videos for content analysis and processing.
Key features:
Extract transcripts from YouTube videos using their URL or ID
Support for multiple languages
Format text with continuous or paragraph mode
Retrieve video metadata including title, ID, language, and duration
Automatic paragraph segmentation
Text normalization and HTML entity decoding
Robust error handling
Enables retrieval of transcripts from YouTube videos with support for multiple languages, formatting options, and metadata extraction including video titles, timestamps, and automatic paragraph segmentation.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-youtube-transcriptget transcript from https://www.youtube.com/watch?v=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.
MCP YouTube Transcript Server
A TypeScript Model Context Protocol server that retrieves YouTube transcripts for Claude Desktop, Cursor, Cline, Codex, and other MCP-compatible clients. It is designed for local npx usage so transcript requests are made from your own machine instead of a remote proxy.
Table of Contents
Related MCP server: YouTube Transcript Server
Features
Key capabilities:
Extract transcripts from YouTube videos
Support for multiple languages
Android InnerTube fallback for current YouTube caption responses
Compatible tool names:
get_transcriptsandget_transcriptTimestamped transcript output with
get_timed_transcriptVideo metadata and available transcript languages
Format text with continuous or paragraph mode
Retrieve video titles and metadata
Automatic paragraph segmentation
Text normalization and HTML entity decoding
Robust error handling
Timestamp and overlap detection
Getting Started
Prerequisites
Node.js 18 or higher
Installation
Use a local npx configuration so transcript requests are sent from your own machine instead of a remote MCP proxy.
Create or edit the Claude Desktop configuration file:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Add the following configuration:
{
"mcpServers": {
"youtube-transcript": {
"command": "npx",
"args": [
"-y",
"@sinco-lab/mcp-youtube-transcript"
]
}
}
}Quick setup script for macOS:
# Create directory if it doesn't exist
mkdir -p ~/Library/Application\ Support/Claude
# Create or update config file
cat > ~/Library/Application\ Support/Claude/claude_desktop_config.json << 'EOL'
{
"mcpServers": {
"youtube-transcript": {
"command": "npx",
"args": [
"-y",
"@sinco-lab/mcp-youtube-transcript"
]
}
}
}
EOLUsage
Basic Configuration
To use with Claude Desktop / Cursor / cline, ensure your configuration matches:
{
"mcpServers": {
"youtube-transcript": {
"command": "npx",
"args": ["-y", "@sinco-lab/mcp-youtube-transcript"]
}
}
}Docker
The repository includes a production Dockerfile for local container usage:
docker build -t mcp-youtube-transcript .MCP client configuration:
{
"mcpServers": {
"youtube-transcript": {
"command": "docker",
"args": ["run", "--rm", "-i", "mcp-youtube-transcript"]
}
}
}Testing
With Claude App
Restart the Claude app after installation
Test with a simple command:
https://www.youtube.com/watch?v=AJpK3YTTKZ4 Summarize this video
Example output:

With MCP Inspector
# Clone and setup
git clone https://github.com/sinco-lab/mcp-youtube-transcript.git
cd mcp-youtube-transcript
npm install
npm run build
# Launch inspector
npx @modelcontextprotocol/inspector node "dist/index.js"
# Access http://localhost:6274 and try these commands:
# 1. List Tools: clink `List Tools`
# 2. Test get_transcripts with:
# url: "https://www.youtube.com/watch?v=AJpK3YTTKZ4"
# lang: "en" (optional; omit to use the best available caption track)
# enableParagraphs: false (optional)Troubleshooting and Maintenance
Checking Claude Logs
To monitor Claude's logs, you can use the following command:
tail -n 20 -f ~/Library/Logs/Claude/mcp*.logThis will display the last 20 lines of the log file and continue to show new entries as they are added.
Note: Claude app automatically prefixes MCP server log files with
mcp-server-. For example, our server's logs will be written tomcp-server-youtube-transcript.log.
Cleaning the npx Cache
If you encounter issues related to the npx cache, you can manually clean it using:
rm -rf ~/.npm/_npxThis will remove the cached packages and allow you to start fresh.
Tools
get_transcripts
Fetches transcript text from a YouTube video.
Parameters:
url(string, required): YouTube video URL or IDlang(string, optional): Language code. If omitted, the best available caption track is used.enableParagraphs(boolean, optional): Enable paragraph mode. Default:false.
get_transcript
Alias of get_transcripts for compatibility with other YouTube transcript MCP servers.
get_timed_transcript
Fetches transcript text with one timestamped line per caption segment.
Parameters:
url(string, required): YouTube video URL or IDlang(string, optional): Language code. If omitted, the best available caption track is used.
Example output:
[00:00:01.250] Hello and welcome
[00:00:03.500] Today we are going to...get_video_info
Fetches basic video metadata and available transcript languages without returning the full transcript.
Parameters:
url(string, required): YouTube video URL or ID
get_available_languages
Lists available transcript languages for a YouTube video. Use this before retrying with a specific lang value.
Parameters:
url(string, required): YouTube video URL or ID
Development
Project Structure
├── src/
│ ├── index.ts # Server entry point
│ ├── youtube.ts # YouTube transcript fetching logic
├── tests/ # Node test runner coverage
├── docs/ # Maintenance notes
├── Dockerfile # Local container build
├── dist/ # Compiled output
└── package.jsonKey Components
YouTubeTranscriptFetcher: Core transcript fetching functionalityYouTubeUtils: Text processing and utilities
Features and Capabilities
Error Handling:
Invalid URLs/IDs
Unavailable transcripts
Language availability
Network errors
Rate limiting
Empty caption responses caused by YouTube client enforcement
Text Processing:
HTML entity decoding
Punctuation normalization
Space normalization
srv3, classic XML,json3, and VTT caption parsingSmart paragraph detection
YouTube Access Notes
YouTube does not provide an official public API for downloading captions from arbitrary videos. This server uses YouTube's internal caption data exposed to web and Android clients. YouTube may still reject requests from some networks, hosted environments, or remote MCP providers. When that happens, the server now returns a more specific diagnostic instead of a generic No transcripts found error.
Contributing
We welcome contributions! Please feel free to submit issues and pull requests.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Related Projects
Available Tools
1 toolget_transcriptsA
Extract and process transcripts from a YouTube video.
Parameters:
url(string, required): YouTube video URL or ID.lang(string, optional, default 'en'): Language code for transcripts (e.g. 'en', 'uk', 'ja', 'ru', 'zh').enableParagraphs(boolean, optional, default false): Enable automatic paragraph breaks.
IMPORTANT: If the user does not specify a language code, DO NOT include the lang parameter in the tool call. Do not guess the language or use parts of the user query as the language code.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | YouTube video URL or ID | |
| lang | No | Language code for transcripts, default 'en' (e.g. 'en', 'uk', 'ja', 'ru', 'zh') | en |
| enableParagraphs | No | Enable automatic paragraph breaks, default `false` |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively explains the tool's core function and includes important behavioral guidance about parameter handling (the IMPORTANT note about not guessing language). However, it doesn't mention potential limitations like video availability, transcript existence, rate limits, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear purpose statement followed by parameter documentation and important usage notes. Every sentence serves a purpose, though the parameter list slightly duplicates schema information. The IMPORTANT section is appropriately emphasized for critical behavioral guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description provides adequate coverage for the tool's basic function and parameters. However, it lacks information about return values, error handling, and operational constraints that would be helpful for an agent. The IMPORTANT note adds valuable context, but more behavioral transparency would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 all parameters thoroughly. The description repeats this information in a bulleted list without adding significant semantic context beyond what's in the schema. The IMPORTANT note about language parameter handling adds some value, but overall the description doesn't enhance parameter understanding beyond the structured schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('extract and process') and resource ('transcripts from a YouTube video'). It distinguishes itself from potential alternatives by focusing on transcript extraction rather than other video-related operations, though no sibling tools exist for direct comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage guidance through the IMPORTANT note about language parameter handling, but it doesn't explicitly state when to use this tool versus alternatives (e.g., when transcripts are needed vs. other video metadata). Since no sibling tools exist, this is less critical, but general context about appropriate use cases is missing.
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 tool update
- First observed
get_transcripts
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'get_transcripts' follows a clear verb_noun pattern.
A single tool is too few for a server focused on YouTube transcripts, as it lacks operations like searching transcripts, managing multiple videos, or handling errors. This minimal scope limits functionality and agent workflows.
The tool set is severely incomplete for the domain of YouTube transcript processing. It only provides extraction (get_transcripts), missing essential operations such as searching within transcripts, listing available languages, or handling video metadata, which are common needs in this context.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
An MCP server that gives any LLM or agent clean YouTube transcripts on demand: a single video, a whole channel, or a playlist, plus AI cleanup of auto-generated captions. API-key auth, credit-based, same backend as the public v1 API. Get a free API key with 25 free credits at youtubetranscriptdownload.com/account.
MCP server for RiverScript, an AI transcription platform - fetches transcripts shared via a link.
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
MCP server for structured access to Lenny Rachitsky podcast transcripts. For content creators.
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- AlicenseBqualityDmaintenanceA Model Context Protocol server that enables AI assistants to extract transcripts from YouTube videos, allowing AI to analyze and work with video content directly.1273MIT
- AlicenseAqualityDmaintenanceA Model Context Protocol server that enables access to YouTube video content through transcripts, translations, summaries, and subtitle generation in various languages.55MIT
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