yt-studio-mcp

yt-studio-mcp

Manage a YouTube channel through official Google APIs — videos, comments, playlists, live broadcasts, captions, and analytics — plus an auditable giveaway suite for comment-entry giveaways with deterministic winner drawing.

Category
Visit Server

README

yt-studio-mcp

An MCP (Model Context Protocol) server for managing a YouTube channel through the official Google APIs — videos, comments and moderation, playlists, live broadcasts, captions, analytics — plus an auditable giveaway suite for running comment-entry giveaways with deterministic, independently verifiable winner drawing.

  • Official APIs only (YouTube Data v3 + YouTube Analytics v2). No scraping.
  • Every mutating tool accepts dry_run=true and returns a preview instead of writing.
  • No secrets in this repo, in logs, or in your MCP client config.

Quick start

1. Create Google credentials (~5 minutes, one time)

  1. Go to console.cloud.google.com, create a project.
  2. APIs & Services → Library: enable YouTube Data API v3 and YouTube Analytics API.
  3. APIs & Services → OAuth consent screen: External, add yourself as a test user.
  4. APIs & Services → Credentials → Create credentials → OAuth client ID → Desktop app; download the JSON as client_secret.json.

2. Authorize your channel

uvx yt-studio-mcp auth --client-secret /path/to/client_secret.json

A browser opens — sign in and pick the channel (Brand Accounts appear as separate choices). The refresh token is stored locally (see Secret storage).

3. Connect your MCP client

# Claude Code
claude mcp add yt-studio -s user -- uvx yt-studio-mcp

Tools

Area Tools
Channel/videos channel_info, list_videos, get_video, update_video, set_thumbnail, upload_video, delete_video
Playlists list_playlists, create_playlist, delete_playlist, add_to_playlist, remove_from_playlist, list_playlist_items
Comments list_comments, post_video_question, reply_to_comment, moderate_comment, mark_spam, delete_comment
Live list_broadcasts, create_broadcast, list_streams, bind_broadcast, live_chat_messages, post_chat_message, delete_chat_message, ban_chat_user
Captions list_captions, upload_caption, download_caption
Analytics channel_report, video_report, top_videos
Giveaways collect_entries, draw_winners, make_verification_code, check_verification_reply, post_winner_reply
Meta quota_status, health_check

Known API limitations (documented, not bugs): comments cannot be pinned via the API (post_video_question reminds you to pin manually in Studio), and Community-tab posts have no public API.

Running a giveaway

The giveaway suite implements a common official-rules pattern: comment on any video during the entry window; each distinct video counts as one entry, capped per person; winners drawn at random.

1. collect_entries(start="2026-01-01T00:00:00Z", end="2026-01-31T23:59:59Z",
                   max_entries_per_user=5, exclude_channel_ids=[...])
     → walks every upload's comments, derives entries, writes a snapshot
       file and returns its SHA-256 entry hash. Announce the hash if you
       want third-party verifiability.

2. draw_winners(snapshot_path, n=5, seed="any-public-string")
     → deterministic: a seeded shuffle over the canonically sorted entries,
       first n distinct channels win. Anyone with the snapshot + seed can
       re-run the draw and get identical winners. Records an audit file.
       Screen-record this step for extra transparency.

3. make_verification_code(audit_path, winner_channel_id)
     → short code you send to the claimed winner over your announced contact
       channel.

4. check_verification_reply(audit_path, comment_id, winner_channel_id)
     → confirms the reply was authored by the winning channel and contains
       the code — proves account ownership before shipping a prize.

5. post_winner_reply(comment_id, "Congratulations! ...")

Entries and audit records live in ~/.config/yt-studio-mcp/giveaways/.

This tool automates entry collection and drawing; giveaway laws vary by jurisdiction and platform policies apply (e.g. YouTube's contest policies). You are responsible for your own official rules and compliance.

Secret storage

Backend Select with Stores
file (default) ~/.config/yt-studio-mcp/credentials.json, chmod 0600
env YT_MCP_SECRETS=env reads YT_MCP_REFRESH_TOKEN, YT_MCP_CLIENT_ID, YT_MCP_CLIENT_SECRET
vaultproxy YT_MCP_SECRETS=vaultproxy (+ VAULTPROXY_URL) items in a Vaultwarden vault via a local vaultproxy HTTP API

Quota

The Data API's default allocation is 10,000 units/day. Most reads cost 1 unit; writes cost ~50; a video upload costs 1,600. quota_status() shows a session estimate and warns at 80%. collect_entries reports what it spent.

Development

pip install -e '.[dev]'
ruff check src tests && pytest

Tests are fully offline (mocked Google API). PRs welcome.

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured