
yutu
Fully automated YouTube workflow automation tool and MCP server.
Key Features
Use Cases
README
yutu
yutu
is a fully functional MCP server and CLI for YouTube to automate your YouTube workflows. It can manipulate almost all YouTube resources, like videos, playlists, channels, comments, captions, and more.
Table of Contents
Prerequisites
Before you begin, an account on Google Cloud Platform is required to create a Project and enable these APIs for this project, in APIs & Services -> Enable APIs and services -> + ENABLE APIS AND SERVICES
After enabling the APIs, create an OAuth content screen
with yourself as test user, then create an OAuth Client ID
of type Web Application
with http://localhost:8216
as the redirect URI.
Download this credential to your local machine with name client_secret.json
, it should look like
{
"web": {
"client_id": "11181119.apps.googleusercontent.com",
"project_id": "yutu-11181119",
"auth_uri": "https://accounts.google.com/o/oauth2/auth",
"token_uri": "https://oauth2.googleapis.com/token",
"auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
"client_secret": "XXXXXXXXXXXXXXXX",
"redirect_uris": [
"http://localhost:8216"
]
}
}
To verify this credential, run the following command
❯ yutu auth --credential client_secret.json
A browser window will open asking for your permission to access your YouTube account, after granting the permission, a token will be generated and saved to youtube.token.json
.
{
"access_token": "ya29.XXXXXXXXX",
"token_type":"Bearer",
"refresh_token":"1//XXXXXXXXXX",
"expiry":"2024-05-26T18:49:56.1911165+08:00"
}
By default, yutu
will read client_secret.json
and youtube.token.json
from the current directory, --credential/-c
and --cacheToken/-t
flags are available only in auth
subcommand. To modify the default path in all subcommands, set these environment variables
❯ export YUTU_CREDENTIAL=client_secret.json
❯ export YUTU_CACHE_TOKEN=youtube.token.json
# or
❯ YUTU_CREDENTIAL=client_secret.json YUTU_CACHE_TOKEN=youtube.token.json yutu subcommand --flag value
Installation
You can download yutu
from releases page directly, or use the following methods as you prefer.
GitHub Actions
There are two actions available for yutu, one is for general purpose and the other is for uploading video to YouTube. Refer to youtube-action and youtube-uploader for more information.
Docker
❯ docker pull ghcr.io/eat-pray-ai/yutu:latest
❯ docker run --rm ghcr.io/eat-pray-ai/yutu:latest
# make sure client_secret.json is in the current directory
❯ docker run --rm -it -u $(id -u):$(id -g) -v $(pwd):/app ghcr.io/eat-pray-ai/yutu:latest auth
Gopher
❯ go install github.com/eat-pray-ai/yutu@latest
Linux
❯ curl -sSfL https://raw.githubusercontent.com/eat-pray-ai/yutu/main/scripts/install.sh | bash
macOS
Install yutu
using Homebrew🍺(recommended), or run the shell script.
❯ brew install yutu
# or
❯ curl -sSfL https://raw.githubusercontent.com/eat-pray-ai/yutu/main/scripts/install.sh | bash
Windows
❯ winget install yutu
Verifying Installation
Verify the integrity and provenance of yutu
using its associated cryptographically signed attestations.
# Docker
❯ gh attestation verify oci://ghcr.io/eat-pray-ai/yutu:latest --repo eat-pray-ai/yutu
# Linux and macOS(if installed using shell script)
❯ gh attestation verify $(which yutu) --repo eat-pray-ai/yutu
# Windows
❯ gh attestation verify $(where.exe yutu.exe) --repo eat-pray-ai/yutu
MCP Server
As a MCP server, yutu
can be used in MCP clients like Claude Desktop, VS Code or Cursor, which allows you to interact with YouTube resources in a chat-like interface.
Before using yutu
as an MCP server, make sure yutu
is installed(see Installation section), and you have a valid client_secret.json
and youtube.token.json
files(refer to Prerequisites section).
You can add yutu
as a MCP server in VS Code or Cursor by clicking corresponding badge above, or add the following configuration manually to your MCP client. Remember to replace the values of YUTU_CREDENTIAL
and YUTU_CACHE_TOKEN
with correct paths on your local machine.
{
"yutu": {
"type": "stdio",
"command": "yutu",
"args": [
"mcp"
],
"env": {
"YUTU_CREDENTIAL": "/absolute/path/to/client_secret.json",
"YUTU_CACHE_TOKEN": "/absolute/path/to/youtube.token.json"
}
}
}
Usage
❯ yutu is a fully functional MCP server and CLI for YouTube, which can manipulate almost all YouTube resources
Usage:
yutu [flags]
yutu [command]
Available Commands:
activity List YouTube activities
auth Authenticate with YouTube API
caption Manipulate YouTube captions
channel Manipulate YouTube channels
channelBanner Insert Youtube channel banner
channelSection Manipulate YouTube channel sections
comment Manipulate YouTube comments
commentThread Manipulate YouTube comment threads
completion Generate the autocompletion script for the specified shell
help Help about any command
i18nLanguage List YouTube i18n languages
i18nRegion List YouTube i18n regions
mcp Start MCP server
member List channel's members' info
membershipsLevel List memberships levels' info
playlist Manipulate YouTube playlists
playlistImage Manipulate YouTube playlist images
playlistItem Manipulate YouTube playlist items
search Search for YouTube resources
subscription Manipulate YouTube subscriptions
superChatEvent List Super Chat events for a channel
thumbnail Set thumbnail for a video
version Show the version of yutu
video Manipulate YouTube videos
videoAbuseReportReason List YouTube video abuse report reasons
videoCategory List YouTube video categories
watermark Manipulate YouTube watermarks
Flags:
-h, --help help for yutu
Use "yutu [command] --help" for more information about a command.
Features
Please refer to FEATURES.md for more information.
Contributing
Please refer to CONTRIBUTING.md for more information.
Star History
Star History
Repository Owner
Organization
Repository Details
Programming Languages
Topics
Join Our Newsletter
Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.
Related MCPs
Discover similar Model Context Protocol servers

k8s-mcp-server
Securely enable Claude to run Kubernetes CLI tools via Anthropic's Model Context Protocol.
K8s MCP Server provides a Docker-based implementation of Anthropic's Model Context Protocol (MCP), allowing Claude to securely execute Kubernetes CLI tools such as kubectl, helm, istioctl, and argocd within a containerized environment. It integrates with Claude Desktop so users can interact with their Kubernetes clusters using natural language. The server emphasizes security by operating as a non-root user and offering strict command validation, while also supporting major cloud providers like AWS, Google Cloud, and Azure. Easy configuration and support for various Unix tools further enhance its capabilities.
- ⭐ 166
- MCP
- alexei-led/k8s-mcp-server

cloudflare/mcp-server-cloudflare
Connect Cloudflare services to Model Context Protocol (MCP) clients for AI-powered management.
Cloudflare MCP Server enables integration between Cloudflare's suite of services and clients using the Model Context Protocol (MCP). It provides multiple specialized servers that allow AI models to access, analyze, and manage configurations, logs, analytics, and other features across Cloudflare's platform. Users can leverage natural language interfaces in compatible MCP clients to read data, gain insights, and perform automated actions on their Cloudflare accounts. This project aims to streamline the orchestration of security, development, monitoring, and infrastructure tasks through standardized MCP connections.
- ⭐ 2,919
- MCP
- cloudflare/mcp-server-cloudflare

awslabs/mcp
Specialized MCP servers for seamless AWS integration in AI and development environments.
AWS MCP Servers is a suite of specialized servers implementing the open Model Context Protocol (MCP) to bridge large language model (LLM) applications with AWS services, tools, and data sources. It provides a standardized way for AI assistants, IDEs, and developer tools to access up-to-date AWS documentation, perform cloud operations, and automate workflows with context-aware intelligence. Featuring a broad catalog of domain-specific servers, quick installation for popular platforms, and both local and remote deployment options, it enhances cloud-native development, infrastructure management, and workflow automation for AI-driven tools. The project includes Docker, Lambda, and direct integration instructions for environments such as Amazon Q CLI, Cursor, Windsurf, Kiro, and VS Code.
- ⭐ 6,220
- MCP
- awslabs/mcp

mcp
Universal remote MCP server connecting AI clients to productivity tools.
WayStation MCP acts as a remote Model Context Protocol (MCP) server, enabling seamless integration between AI clients like Claude or Cursor and a wide range of productivity applications, such as Notion, Monday, Airtable, Jira, and more. It supports multiple secure connection transports and offers both general and user-specific preauthenticated endpoints. The platform emphasizes ease of integration, OAuth2-based authentication, and broad app compatibility. Users can manage their integrations through a user dashboard, simplifying complex workflow automations for AI-powered productivity.
- ⭐ 27
- MCP
- waystation-ai/mcp

mcp-server-templates
Deploy Model Context Protocol servers instantly with zero configuration.
MCP Server Templates enables rapid, zero-configuration deployment of production-ready Model Context Protocol (MCP) servers using Docker containers and a comprehensive CLI tool. It provides a library of ready-made templates for common integrations—including filesystems, GitHub, GitLab, and Zendesk—and features intelligent caching, smart tool discovery, and flexible configuration options via JSON, YAML, environment variables, or CLI. Perfect for AI developers, data scientists, and DevOps teams, it streamlines the process of setting up and managing MCP servers and has evolved into the MCP Platform for enhanced capabilities.
- ⭐ 5
- MCP
- Data-Everything/mcp-server-templates

mcpmcp-server
Seamlessly discover, set up, and integrate MCP servers with AI clients.
mcpmcp-server enables users to discover, configure, and connect MCP servers with preferred clients, optimizing AI integration into daily workflows. It supports streamlined setup via JSON configuration, ensuring compatibility with various platforms such as Claude Desktop on macOS. The project simplifies the connection process between AI clients and remote Model Context Protocol servers. Users are directed to an associated homepage for further platform-specific guidance.
- ⭐ 17
- MCP
- glenngillen/mcpmcp-server
Didn't find tool you were looking for?