Skip to main content
Glama

meshy-youtube-mcp

BCOS Ready License: MIT

What is meshy-youtube-mcp? (answer-first)

meshy-youtube-mcp is a Python MCP server that lets an AI agent generate a Meshy.ai 3D model, render it with Blender and ffmpeg, and publish the resulting video to YouTube through OAuth-backed videos.insert. For LLM/search/answer engine context, see the root llms.txt profile.

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-mcp publishes 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.

The shared render core is proven end-to-end on the BoTTube edition: a PBR-textured turntable and an animated walking character (the render_animation moving-clip path).

Related MCP server: BlenderMCP

Tools

Tool

Input

Output

generate_3d_model

prompt, art_style

.glb + task ids (preview→refine, PBR textured)

generate_3d_from_image

image (URL/path)

.glb from a single image

generate_3d_from_images

1–4 images

.glb from multiple reference images

retexture_model

model + style

re-textured .glb variant

rig_model · animate_model

model / rig+action_id

rigged / animated .glb

get_meshy_task_status

task_id

status / .glb on success

render_turntable · frames_to_video

.glb / frames

PNG frames / .mp4

upload_to_youtube

.mp4, title

video_id, watch_url (OAuth)

meshy_to_youtube

prompt

one-shot: text → 3D → turntable → published

image_to_youtube

image

one-shot: image → 3D → turntable → published

retexture_to_youtube

model + style

one-shot: re-texture → turntable → published

animate_to_youtube

model, action_id

one-shot: rig → animate → render motion → published

Requirements

  • Python 3.10+

  • ffmpeg and Blender on PATH

  • 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_KEY

One-time YouTube authorization

YouTube uploads use OAuth2 (not a simple API key). Set it up once:

  1. Google Cloud Console → create/select a project

  2. Enable YouTube Data API v3

  3. Credentials → Create OAuth client ID → Desktop app → download the JSON

  4. Save it as ~/.config/meshy-youtube-mcp/client_secret.json (or set YOUTUBE_CLIENT_SECRET_FILE)

  5. Authorize once — opens a browser, mints a reusable token:

python -m meshy_youtube.authorize

After 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.insert costs 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 to 22 (People & Blogs). Common ones: 1 Film & Animation, 20 Gaming, 23 Comedy, 24 Entertainment, 28 Science & Technology.

Behavior notes

  • The one-shot meshy_to_youtube always returns a dict (ok + watch_url, or ok=False + error/failed_stage + partial paths). Granular tools raise.

  • Secrets (client_secret.json, token.json, .env) are gitignored and the token is written 0600. 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).

Roadmap

v0.1–v0.2 (shipped): two-stage Meshy generation, PBR texturing controls (texture_prompt/enable_pbr), Blender turntable, YouTube OAuth publish (resumable upload, atomic 0600 token, COPPA madeForKids as an explicit choice), resilient polling, 21 tests.

v0.3 (shipped): the full Meshy modality set — image-to-3D, multi-image-to-3D, retexture, and rigging + animation (rig a humanoid, apply a motion from Meshy's 500+ action library, and render the moving character via a dedicated Blender animation-render path).

Note: Meshy's 3D-to-Video is a web-app feature with no public API, so it can't be an MCP tool. The rig→animate→render chain delivers the same outcome.

Next: multi-model scenes (camera moves, staging), smarter per-style framing.

Tests

python -m unittest discover -s tests -v

License

MIT © 2026 Scott Boudreaux / Elyan Labs.

A
license - permissive license
-
quality - not tested
B
maintenance

Maintenance

Maintainers
Response time
Release cycle
Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Servers

View all related MCP servers

Related MCP Connectors

  • Generate, edit, and deploy immersive 3D/WebGL web projects from any MCP assistant.

  • MCP server for Google Veo AI video generation

  • MCP server for OpenAI Sora AI video generation

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Scottcjn/meshy-youtube-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server