yutu MCP Server
io.github.eat-pray-ai/yutu
AI-powered toolkit to automate YouTube workflows—upload, optimize, manage comments and playlists on autopilot.
What is the yutu MCP server?
The yutu MCP server is a CLI, MCP server, and AI agent for YouTube that automates your entire YouTube workflow from uploading and optimizing videos to managing comments, playlists, and channel branding. It integrates with Claude and Cursor to give AI agents direct access to YouTube operations, enabling automated growth strategies with less manual effort.
yutu automates YouTube channel management through a multi-agent architecture with specialized agents for retrieval, modification, and deletion of YouTube content. Use it to upload videos, optimize metadata for SEO, manage comments and playlists, set thumbnails, handle captions, and execute growth strategies—all via AI agents or CLI commands.
How to install yutu
Copy-paste configuration for popular MCP clients.
YUTU_CREDENTIALrequiredsecretGCP project credential for yutu, Base64 encoded JSON or path to JSON file
YUTU_CACHE_TOKENrequiredsecretYouTube authentication token, Base64 encoded JSON or path to JSON file
YUTU_LOG_LEVELLog level
Tools & capabilities
Tools this server exposes to the agent.
Video Upload— Upload videos to YouTube with metadata optimizationVideo Search & List— Search and list videos from your channelMetadata Management— Update video titles, descriptions, tags, and other metadataPlaylist Management— Create and manage playlistsComment Management— Post and manage comments on videosThumbnail Management— Set custom thumbnails for videosCaption Management— Manage video captions and subtitlesWatermark Management— Add and manage channel watermarksChannel Data Retrieval— Access channel information, subscriptions, and membersAnalytics Access— Retrieve YouTube Analytics and reporting dataVideo Deletion— Delete videos from your channelPlaylist Deletion— Delete playlistsComment Deletion— Delete commentsGoogle Search— Search the web for research and SEO insights
Use cases
- Automate video uploads with optimized titles, descriptions, and tags for better SEO and discoverability
- Manage channel comments and engagement at scale by posting and moderating comments programmatically
- Create and organize playlists automatically based on video content and audience segments
- Generate growth strategies and execute them through AI agents that coordinate multiple YouTube operations
- Monitor channel analytics and performance metrics to inform content decisions
yutu MCP server FAQ
yutu is a CLI, MCP server, and AI agent for YouTube that automates your entire YouTube workflow—from uploading and optimizing videos to managing comments, playlists, and channel branding. It works with Claude, Cursor, and other AI tools via the Model Context Protocol.
yutu is open-source (Apache 2.0 license) and free to use. However, you need a Google Cloud Platform account with YouTube Data API enabled to authenticate and access YouTube.
Install yutu via npm (`npm i -g @eat-pray-ai/yutu`), then add it as an MCP server in Cursor or Claude using the provided deeplinks or by manually configuring it with your `client_secret.json` and `youtube.token.json` paths in your MCP settings.
You need a Google Cloud Platform account with YouTube Data API v3 enabled. Create OAuth credentials (Desktop app), download `client_secret.json`, then run `yutu auth --credential client_secret.json` to generate `youtube.token.json`.
Yes. yutu includes a multi-agent system with an orchestrator and specialized agents (Retrieval, Modifier, Destroyer) that can autonomously plan and execute YouTube workflows. Set `YUTU_ADVANCED_MODEL` and `YUTU_LITE_MODEL` environment variables to use Google Gemini models.
yutu runs on Linux, macOS, Windows, Docker, and Node.js. Install via Homebrew (macOS), winget (Windows), npm, or download directly from the releases page.
README (reference)
Source of truth, from the repository.
yutu
yutu is a CLI, MCP server, and AI agent for YouTube that automates your entire YouTube workflow — from uploading and optimizing videos to managing comments, playlists, and channel branding — so you can get more views, higher click-through rates, and stronger audience engagement with less manual effort. 中文文档
Table of Contents
Prerequisites
An account on Google Cloud Platform is required. Set up the following:
-
Create a GCP Project and enable these APIs under
APIs & Services -> Enable APIs and services:- YouTube Data API v3 (Required)
- YouTube Analytics API (Optional)
- YouTube Reporting API (Optional)
-
Create OAuth credentials:
- Go to
APIs & Services -> OAuth consent screen, create a consent screen with yourself as a test user - Go to
Credentials -> Create Credentials -> OAuth Client ID, selectDesktop app - Download the credential file and save it as
client_secret.json, it should look like
{ "installed": { "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" ] } } - Go to
-
Authenticate:
yutu auth --credential client_secret.jsonA browser window will open for you to grant YouTube access. After granting permission, a token is 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", "expires_in": 3599 }
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.
Global Environment Variables
| Variable | Description | Default |
|---|---|---|
YUTU_CREDENTIAL | Path, Base64, or JSON of OAuth client secret | client_secret.json |
YUTU_CACHE_TOKEN | Path, Base64, or JSON of cached OAuth token | youtube.token.json |
YUTU_ROOT | Root directory for file resolution | Current working directory |
YUTU_LOG_LEVEL | Log level: DEBUG, INFO, WARN, ERROR | INFO |
Installation
You can download yutu from releases page directly, or use the following methods as you prefer.
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.
</details> <details> <summary>Node.js</summary>❯ npm i -g @eat-pray-ai/yutu
</details>
<details>
<summary>Docker</summary>
❯ 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 -p 8216:8216 ghcr.io/eat-pray-ai/yutu:latest
</details>
<details>
<summary>Gopher</summary>
❯ go install github.com/eat-pray-ai/yutu@latest
</details>
<details>
<summary>Linux</summary>
❯ curl -sSfL https://raw.githubusercontent.com/eat-pray-ai/yutu/main/scripts/install.sh | bash
</details>
<details>
<summary>macOS</summary>
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
</details>
<details>
<summary>Windows</summary>
❯ winget install yutu
</details>
<details>
<summary>Verifying Installation</summary>
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
</details>
Agent
yutu provides an agent mode to automate YouTube workflows. The system uses a multi-agent architecture where a central orchestrator delegates tasks to specialized agents:
| Agent | Role | Capabilities |
|---|---|---|
| Orchestrator | Coordinates the entire workflow, plans strategy, and delegates to sub-agents | YouTube growth strategy, SEO optimization, task routing |
| Retrieval | Gathers data from YouTube and the web (read-only) | List/search videos, channels, playlists, comments, captions, subscriptions, members, and more; Google Search |
| Modifier | Creates and updates YouTube content | Upload videos, create playlists, update metadata, post comments, set thumbnails, manage captions and watermarks |
| Destroyer | Handles destructive operations with extra caution | Delete videos, playlists, comments, captions, subscriptions, channel sections, and watermarks |
Currently, the agent mode is under active development, only supports Google's Gemini models with the following environment variables set:
❯ export YUTU_ADVANCED_MODEL=google:gemini-3.1-pro-preview
❯ export YUTU_LITE_MODEL=google:gemini-3-flash-preview
❯ export YUTU_LLM_API_KEY=your_gemini_api_key
// Optional settings
❯ export GOOGLE_GEMINI_BASE_URL=https://generativelanguage.googleapis.com/
❯ export YUTU_AGENT_INSTRUCTION=Your custom instruction here
YUTU_ADVANCED_MODEL is used by the orchestrator agent, while YUTU_LITE_MODEL is used by all other agents. Both use
the provider:modelName format (only google is supported). If only one is set, the other defaults to the same value.
Agent Environment Variables
| Variable | Description | Required |
|---|---|---|
YUTU_ADVANCED_MODEL | Model for orchestrator agent (format: provider:modelName) | At least one of YUTU_ADVANCED_MODEL or YUTU_LITE_MODEL |
YUTU_LITE_MODEL | Model for sub-agents (format: provider:modelName) | At least one of YUTU_ADVANCED_MODEL or YUTU_LITE_MODEL |
YUTU_LLM_API_KEY | API key for the model provider | Yes |
GOOGLE_GEMINI_BASE_URL | Base URL for Gemini API | No |
YUTU_AGENT_INSTRUCTION | Custom instruction for orchestrator agent | No |
YUTU_RETRIEVAL_INSTRUCTION | Custom instruction for retrieval agent | No |
YUTU_MODIFIER_INSTRUCTION | Custom instruction for modifier agent | No |
YUTU_DESTROYER_INSTRUCTION | Custom instruction for destroyer agent | No |
Then run the following command for detail usage:
❯ yutu agent --help
❯ yutu agent --args "help"
# console mode
❯ yutu agent --args "console"
# web mode with three sub-launchers: api, a2a and webui
❯ yutu agent --args "web api a2a webui"
MCP Server
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 an MCP server in VS Code or Cursor by clicking corresponding badge, or use the CLI commands below for your preferred tool.
# Stdio mode
❯ claude mcp add -e YUTU_CREDENTIAL=/absolute/path/to/client_secret.json \
-e YUTU_CACHE_TOKEN=/absolute/path/to/youtube.token.json \
yutu -- yutu mcp
# HTTP mode (start the server first: yutu mcp --mode http --auth)
❯ claude mcp add --transport http \
--client-id YOUR_CLIENT_ID.apps.googleusercontent.com \
--client-secret \
yutu http://localhost:8216/mcp
</details>
<details>
<summary>Codex</summary>
# Stdio mode
❯ codex mcp add --env YUTU_CREDENTIAL=/absolute/path/to/client_secret.json \
--env YUTU_CACHE_TOKEN=/absolute/path/to/youtube.token.json \
yutu -- yutu mcp
# HTTP mode (start the server first: yutu mcp --mode http --auth)
❯ codex mcp add --url http://localhost:8216/mcp \
--oauth-client-id YOUR_CLIENT_ID.apps.googleusercontent.com \
yutu
</details>
<details>
<summary>Manual Configuration (VS Code, Cursor, OpenCode, etc.)</summary>
Add the following to your MCP settings. 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"
}
}
}
</details>
Skills
yutu provides a unified skill that extends AI agents with YouTube domain knowledge, common workflows, and SEO best practices — covering videos, playlists, comments, channels, captions, subscriptions, and more.
❯ npx skills add https://github.com/eat-pray-ai/yutu/tree/main/skills/youtube
See skills/youtube/SKILL.md for the full list of supported operations.
Usage
❯ yutu
yutu is a CLI, MCP server, and AI agent for YouTube that can automate almost all YouTube workflows.
Environment variables:
YUTU_CREDENTIAL Path/Base64/JSON of OAuth client secret (default: client_secret.json)
YUTU_CACHE_TOKEN Path/Base64/JSON of cached OAuth token (default: youtube.token.json)
YUTU_ROOT Root directory for file resolution (default: current working directory)
YUTU_LOG_LEVEL Log level: DEBUG, INFO, WARN, ERROR (default: INFO)
Usage:
yutu [flags]
yutu [command]
Available Commands:
activity Manage activities on YouTube
agent Start an agent to automate YouTube workflows
auth Authenticate with YouTube APIs
caption Manage YouTube video captions
channel Manage YouTube channels
channelBanner Manage YouTube channel banners
channelSection Manage YouTube channel sections
comment Manage YouTube comments
commentThread Manage YouTube comment threads
completion Generate the autocompletion script for the specified shell
help Help about any command
i18nLanguage Manage YouTube i18n languages
i18nRegion Manage YouTube i18n regions
mcp Start MCP server
member Manage YouTube channel members
membershipsLevel Manage YouTube memberships levels
playlist Manage YouTube playlists
playlistImage Manage YouTube playlist images
playlistItem Manage YouTube playlist items
search Manage YouTube search
subscription Manage YouTube subscriptions
superChatEvent Manage YouTube Super Chat events
thirdPartyLink Manage YouTube third-party links
thumbnail Manage YouTube video thumbnails
version Show the version of yutu
video Manage YouTube videos
videoAbuseReportReason Manage YouTube video abuse report reasons
videoCategory Manage YouTube video categories
watermark Manage 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
Related MCP servers

io.github.ebadros/sidearm
Protect media from AI training, detect AI-generated content, and find stolen work.

Lians Agent Memory
Bitemporal memory for AI agents with point-in-time recall and tamper-evident audit history.

io.github.ebenezer-isaac/llmconveyors
53 tools for LLM Conveyors: job hunting, B2B sales, ATS scoring, resume tools.

Google Tasks MCP Server
Manage Google Tasks from MCP-compatible AI clients.
Real-time ESPN sports data: live scores, standings, boxscores, odds & stats for 25+ leagues
Real-time global news, crypto, weather & earthquakes from 27 free APIs. No API keys required.
View repository →
