Does yt-dlp-mCP require yt-dlp to be installed separately?
Yes. You must install yt‑dlp using `winget` (Windows), `brew` (macOS), or `pip` (Linux) before using the server.
@kevinwatt
Basic information
A Model Context Protocol (MCP) server that bridges Video & Audio content with Large Language Models using yt-dlp.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"yt-dlp": {
"command": "npx",
"args": [
"-y",
"@kevinwatt/yt-dlp-mcp@latest"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
yt-dlp-mcp is a Model Context Protocol server that integrates yt-dlp with MCP-compatible AI systems like Claude and Dive. It lets you search videos, download content, extract metadata, get transcripts, and more — all through natural language commands.
Install yt‑dlp on your system first, then add the npx configuration to your MCP client. Tools are prefixed with ytdlp_ and are invoked by the AI agent based on natural language prompts. Environment variables let you customize downloads directory, default resolution, subtitle language, and character limits.
Yes. You must install yt‑dlp using `winget` (Windows), `brew` (macOS), or `pip` (Linux) before using the server.
Configure cookies by setting the `YTDLP_COOKIES_FROM_BROWSER` environment variable (e.g., `chrome`) or providing a cookie file path. This requires a JavaScript runtime (deno) to be installed.
Downloads are saved to `~/Downloads` by default. You can change the directory via the `YTDLP_DOWNLOADS_DIR` environment variable.
Yes. The server enforces a default character limit of 25,000 for outputs and a maximum transcript length of 50,000 characters, both adjustable via environment variables.
The server does not perform any tracking or analytics. All downloads happen directly via yt‑dlp, and inputs are validated with Zod schemas for LLM safety.

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