Trellis MCP Server

Trellis MCP Server bridges the gap between AI assistants and Microsoft’s open‑source text‑to‑3D engine, Trellis. By exposing Trellis through the Model Context Protocol (MCP), it allows tools like Claude, Cursor, or Windsurf to request 3‑D asset generation and texture creation as if they were native API calls. This eliminates the need for costly third‑party services and keeps development costs low while still delivering high‑quality, GPU‑accelerated 3‑D content.

The server solves a critical pain point for developers who want to integrate generative 3‑D workflows into their AI pipelines without relying on proprietary cloud APIs. Trellis is lightweight enough to run locally on a single machine with 8 GB of GPU VRAM, and it can produce a fully textured mesh from a natural‑language prompt in roughly 15 seconds. This speed, combined with the fact that it is free and open source, makes it an attractive alternative to commercial solutions like Rodin or Tripo.

Key capabilities include:

• Text‑to‑3D generation: Accepts natural language prompts, forwards them to the Trellis API, and returns a ready‑to‑import 3‑D asset for Blender.
• Texture/Material synthesis (planned): Generates high‑quality materials from text for existing meshes, expanding the creative possibilities.
• Blender integration: The MCP server is launched directly from a Trellis‑specific Blender addon, ensuring seamless import of generated assets into the 3‑D workspace.

Real‑world use cases span rapid prototyping, game asset creation, AR/VR content pipelines, and generative design workflows. A product designer can ask an AI assistant to “create a futuristic chair with organic curves,” receive a textured mesh instantly, and drop it into Blender for further refinement—all without leaving the AI chat. Similarly, a game studio can batch‑generate environment props by feeding a list of prompts to the MCP server, streamlining production and reducing manual modeling time.

Integration into AI workflows is straightforward: the MCP server registers itself in the assistant’s configuration, and the client can invoke it using standard calls. Because MCP handles context propagation automatically, developers can chain the 3‑D generation step with downstream tasks such as rendering, physics simulation, or export to game engines. The server’s lightweight design also means it can run on modest hardware, making it suitable for both local development and cloud‑based CI pipelines.

What sets Trellis MCP apart is its combination of speed, low memory footprint, and zero cost. While other MCP services for 3‑D generation often require expensive API subscriptions or heavyweight GPU clusters, Trellis MCP delivers comparable quality on a single consumer‑grade GPU. This makes it an ideal choice for indie developers, research labs, and anyone looking to experiment with generative 3‑D content without incurring significant infrastructure expenses.