meshy-youtube-mcp
Renders 360° turntable animations from 3D models (GLB format) into PNG frames.
Converts rendered PNG frames into a video file (.mp4) for upload.
Uploads videos to YouTube with configurable title, description, tags, and privacy settings.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@meshy-youtube-mcpGenerate a 3D steampunk robot and upload it as an unlisted turntable video to YouTube."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
meshy-youtube-mcp
An MCP server that takes a text prompt all the way to a published YouTube video: Meshy.ai 3D generation → Blender turntable → YouTube upload.
prompt ──▶ Meshy text-to-3D ──▶ Blender 360° turntable ──▶ ffmpeg ──▶ YouTube videos.insert
(.glb model) (PNG frames) (.mp4) (published video)Any MCP-capable agent — Claude, or anything that speaks MCP — can call it to generate rotating 3D content and publish it straight to YouTube.
Sibling project:
meshy-bottube-mcppublishes the same pipeline to BoTTube (a video network for AI agents). BoTTube is the agent-native channel; YouTube is the human-reach channel — same Meshy generation, two audiences. Pick the publisher that fits who's watching.
Tools
Tool | Input | Output |
| prompt, art_style |
|
| task_id | status / |
|
| PNG frames (needs Blender) |
| frames dir |
|
|
|
|
| prompt, title | one-shot full pipeline → |
Related MCP server: BlenderMCP
Requirements
Python 3.10+
A Meshy.ai API key
A Google account + a YouTube OAuth client (one-time setup, below)
Install
git clone https://github.com/Scottcjn/meshy-youtube-mcp
cd meshy-youtube-mcp
pip install -r requirements.txt
cp .env.example .env # add your MESHY_API_KEYOne-time YouTube authorization
YouTube uploads use OAuth2 (not a simple API key). Set it up once:
Google Cloud Console → create/select a project
Enable YouTube Data API v3
Credentials → Create OAuth client ID → Desktop app → download the JSON
Save it as
~/.config/meshy-youtube-mcp/client_secret.json(or setYOUTUBE_CLIENT_SECRET_FILE)Authorize once — opens a browser, mints a reusable token:
python -m meshy_youtube.authorizeAfter that, uploads run unattended via the stored refresh token. You only re-authorize if the token is revoked or deleted.
Quota: YouTube's default free quota is 10,000 units/day and a
videos.insertcosts 1,600 — about 6 uploads/day. Request more in the Cloud Console if you need it.
Run as an MCP server
{
"mcpServers": {
"meshy-youtube": {
"command": "python3",
"args": ["/path/to/meshy-youtube-mcp/meshy_youtube/server.py"],
"env": {
"MESHY_API_KEY": "your_meshy_key",
"YOUTUBE_TOKEN_FILE": "/home/you/.config/meshy-youtube-mcp/token.json"
}
}
}
}Then ask your agent: "Generate a 3D crystal dragon and publish it to YouTube as
an unlisted turntable." It calls meshy_to_youtube and hands back a watch URL.
You can also pip install -e . and run meshy-youtube-mcp, or
python -m meshy_youtube.server.
Use as a library
from meshy_youtube import meshy, turntable, video, youtube
info = meshy.generate("a steampunk robot", "model.glb", art_style="realistic")
tt = turntable.render(info["glb_path"], "frames/", resolution=1080)
mp4 = video.frames_to_video(tt["frames_dir"], "turntable.mp4")
res = youtube.upload(mp4, title="Steampunk Robot — 3D Turntable",
tags=["3d", "meshy"], privacy="unlisted")
print(res["watch_url"])Privacy & categories
privacy:public|unlisted|private(default unlisted — shareable by link, not surfaced publicly until you choose to).category_id: YouTube category. Defaults to22(People & Blogs). Common ones:1Film & Animation,20Gaming,23Comedy,24Entertainment,28Science & Technology.
Behavior notes
The one-shot
meshy_to_youtubealways returns a dict (ok+watch_url, orok=False+error/failed_stage+ partial paths). Granular tools raise.Secrets (
client_secret.json,token.json,.env) are gitignored and the token is written0600. Never commit them.The Meshy/Blender/ffmpeg stages are shared, hardened code from the BoTTube edition (two-stage preview→refine, atomic GLB download, subprocess isolation, numeric frame normalization, bounds + preflight).
Tests
python -m unittest discover -s tests -vLicense
MIT © 2026 Scott Boudreaux / Elyan Labs.
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