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YouTube

by Klavis-AI

Connects AI agents to YouTube for transcripts, video metadata, search, channel details, and playlist contents.

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Install YouTube

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "klavis-ai-youtube": {
      "command": "uvx",
      "args": [
        "klavis"
      ],
      "env": {
        "API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

We couldn’t confirm it starts correctly

We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

uvx klavis

Process exited before answering initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 4d ago.

Overview

Klavis-AI/YouTube provides MCP tools for retrieving YouTube transcripts, video details, metadata, channel information, and playlist contents through the YouTube Data API. It supports a hosted Klavis deployment through the Python or npm SDK, as well as Docker-based self-hosting. Reach for it when an agent needs to search YouTube or extract structured information from videos, channels, or playlists.

Use cases

  • Retrieve transcripts for video analysis
  • Search YouTube videos by keywords and filters
  • Extract titles, descriptions, and statistics
  • Inspect channel videos and metadata
  • Read playlist contents and metadata

Key features

  • Timestamped video transcript retrieval
  • Video metadata and statistics lookup
  • Keyword and filter-based video search
  • Channel details and video listings
  • Playlist contents and metadata access
  • Hosted or Docker deployment

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked Today

Recent health check succeeded.

30/30 checks healthy over the last 76d

Supply-chain signal

1 high-severity advisory on record for this package. Most advisories affect transitive dependencies and may not be exploitable in this server's actual usage — this is a directional signal, not a security audit.

Critical 0High 1Medium 0Low 0

Scanned 8d ago via OSV.dev · klavis (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars5.8kStargazers on the source repository.
Last commit4mo agoMost recent push to the default branch.
Install checkInconclusiveDidn't respond in our test window — often a slow first install.
Directory activity4 viewsConfig copies, upvotes, and views on AllMCPs.

How YouTube works

What Klavis-AI/YouTube does

Klavis-AI/YouTube connects MCP clients and agent applications with YouTube data. Its tool set covers several common retrieval tasks: obtaining video transcripts with timestamps, reading video details and metadata, searching for videos, inspecting channels and their video listings, and accessing playlist contents and metadata.

The server is suited to workflows that need YouTube information in an agent-readable form. For example, an agent can locate videos by keywords, gather a video's title and description, retrieve available transcript text, or inspect the videos associated with a channel or playlist.

How it works

Requests are handled through the YouTube Data API. The server can be accessed through Klavis's hosted infrastructure or run as a container for self-hosting. The hosted route is initialized through the Klavis SDK: applications create a Klavis client with a Klavis API key and then request a YouTube server instance for a user.

For local or controlled deployments, the published Docker image runs the YouTube MCP server and maps its service to port 5000. The container receives an API key through an environment variable and uses a YouTube Data API key configured through Google Cloud.

Setup and configuration

The hosted option requires installing the Klavis package for Python or npm and obtaining a Klavis API key. The server instance is created by selecting the YOUTUBE service and providing a user identifier.

Self-hosting requires Docker and the image ghcr.io/klavis-ai/youtube-mcp-server:latest. Start the container with port 5000 exposed and pass the API key through API_KEY:

Terminal
docker pull ghcr.io/klavis-ai/youtube-mcp-server:latest
docker run -p 5000:5000 -e API_KEY=$API_KEY \
  ghcr.io/klavis-ai/youtube-mcp-server:latest

Create the YouTube credential in Google Cloud Console and enable YouTube Data API v3 before using the self-hosted deployment.

Tools and capabilities

  • Retrieve full video transcripts, including timestamps.
  • Read video details such as titles, descriptions, and statistics.
  • Search YouTube videos using keywords and filters.
  • Get channel details and lists of channel videos.
  • Access playlist contents and playlist metadata.

Limitations and notes

The server depends on YouTube Data API v3, so the relevant Google Cloud API must be enabled for self-hosted use. Hosted deployments use Klavis infrastructure and require a Klavis API key. The repository is licensed under Apache 2.0.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about YouTube

Klavis-AI/YouTube is an MCP server that connects AI agents to YouTube through the YouTube Data API. Its main tools retrieve timestamped video transcripts, video details and metadata, search videos, inspect channel information and listings, and access playlist contents and metadata.

Install it either through the Klavis Python or npm package for hosted access, or run the published Docker image for self-hosting. Hosted usage requires a Klavis API key; Docker usage uses the `ghcr.io/klavis-ai/youtube-mcp-server:latest` image.

Self-hosted deployments require a YouTube Data API key, passed to the container through `API_KEY`. Create the key in Google Cloud Console and enable YouTube Data API v3. Hosted deployments use a Klavis API key when creating the server instance.

It can retrieve video transcripts with timestamps, video details including titles, descriptions, and statistics, search results, channel details and video listings, and playlist contents and metadata.

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