Google Analytics MCP
GA4 MCP server for AI agents: schema discovery, server-side aggregation, analysis-ready defaults.
Description from the maker (original English)
An MCP server retrieving transcripts of YouTube videos
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We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 5, 2026
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Code last changed yesterday
Uses MIT
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed yesterday, and the latest version (0.8.3) reached the registry 8 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.
In the same category: Google Analytics MCP, BibiGPT YouTube Video Summarizer, gtm-api: LinkedIn MCP Server
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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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English | 日本語
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.
[!NOTE]
You'll need
uvinstalled on your system to useuvxcommand.
This server communicates via standard stdio. Most MCP clients can run it directly using uvx (part of Astral uv).
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" ] } } }
<details>
Client-Specific Setup Guides (Click to expand)
.mcpb bundle from the Releases page and drop it into your Claude Desktop Settings.claude_desktop_config.json (restart Claude Desktop after saving):~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonyoutube-transcript, Type: command.uvx --from git+https://github.com/jkawamoto/mcp-youtube-transcript mcp-youtube-transcriptPlease refer to this tutorial for detailed installation instructions: YouTube Transcript Extension.
To configure this server for LM Studio, click the button below.
A Docker image for this server is available on Docker Hub. Please refer to the Docker Hub page for detailed usage instructions and documentation.
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. |
Tool Parameters & Schema
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.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.url (*string, required*): Full YouTube video URL.url (*string, required*): Full YouTube video URL.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" ] } } }
YouTube aggressively blocks automated transcript requests from cloud providers and data center IPs. Using residential or rotating proxies ensures uninterrupted access.
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`)*
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.
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.
This application is licensed under the MIT License. See the LICENSE file for more details.