Skip to main content

MCP (Model Control Protocol) integration for Trellis

Project description

Trellis MCP Server

Trellis MCP provides an interface between AI assistants and Trellis via Model Context Protocol (MCP).

Disclaimer

This project shows a very minimal integration of MCP with Trellis: a lightweight and opensource text-to-3d/image-to-3d 3DAIGC model. Compared with existing rodin integration in blender-mcp and tripo integration, it has following advantages:

  • Faster and memory-efficient: You can deploy the TRELLIS API on your own PC with only 8GPU+ VRAM, while can generate a textured mesh from text in only ~15s.
  • FREE: You DON'T have to pay expensive API from Rodin/Meshy/Tripo.

BUT IT HAS FOLLOWING LIMITATIONS:

  • Trellis is open-source and there is no off-the-shelf API model providers, you have to deploy it by yourself (refer to README).
  • The API/Prompt has NOT been fully tested/tuned, may suffer from stability issues.

So use it at your own risk.

Features

  • Generate 3D asset from natural language(TEXT) using Trellis API and import into blender
  • Generate texture/materials from natural language(TEXT) for a given 3D mesh using Trellis API and import into blender

Roadmap

Prerequisites

Installation

1. Trellis blender addon

  1. Download Trellis Blender Addon from here
  2. Open Blender -> Edit -> Preferences -> Add-ons -> Install from file -> Select the downloaded addon -> Install
  3. In 3D Viewport -> View3D > Sidebar > TRELLIS -> Start MCP Server

2. Configure API backend

As trellis is a free open-source text-to-3d model, you need to deploy your own trellis API backend with reference to README

# clone an API fork of trellis 
git clone https://github.com/FishWoWater/TRELLIS
cd TRELLIS

# EDIT BACKEND URL in trellis_api/config.py

# configure the # of text workers and start ai worker
python trellis_api/ai_worker.py --text-workers-per-gpu 1 --image-workers-per-gpu 0

# start web server 
python trellis_api/web_server.py 

3. Configure the MCP server on Windsurf/Cursor/Claude

# first install uv
# on mac os 
# brew install uv  
pip install uv 

# paste into windsurf mcp servers 
"""
{
    "mcpServers": {
        "blender": {
            "command": "uvx",
            "args": [
                "trellis-mcp"
            ]
        }
    }
}
"""

# for debugging 
git clone https://github.com/FishWoWater/trellis-mcp
uv run main.py 

Acknowledgements

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

trellis_mcp-0.1.1.tar.gz (14.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

trellis_mcp-0.1.1-py3-none-any.whl (14.4 kB view details)

Uploaded Python 3

File details

Details for the file trellis_mcp-0.1.1.tar.gz.

File metadata

  • Download URL: trellis_mcp-0.1.1.tar.gz
  • Upload date:
  • Size: 14.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.10

File hashes

Hashes for trellis_mcp-0.1.1.tar.gz
Algorithm Hash digest
SHA256 10256e07b9867e80846a9ff52f57340535a8a18d38e485bd5ebbb6848c58883c
MD5 6ce515a3fc35dde5304353e2a28475e3
BLAKE2b-256 463d1b1cb44c79b1216b7350d68e9a5036df081ab0a0f97cb71632dbc619be7b

See more details on using hashes here.

File details

Details for the file trellis_mcp-0.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for trellis_mcp-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 b1800665437ba7fb71772ea84106b0ee395a7902ffee02b337f411b19f3dc38b
MD5 0c385c8a96c89f21ec35a7ddf426429e
BLAKE2b-256 bbdd7e0ebbcf6ac5d166ac69ec187803fcfbcae822579ec88e08e4eae381cb1a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page