Meshy AI MCP Server

MCP Server

Generate and refine 3D models via text, images, and textures

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About

An MCP server that interfaces with Meshy AI to create 3D models from text or images, apply textures, remesh and optimize them, while providing real‑time task streaming and balance checks.

Capabilities

Resources

Access data sources

Tools

Execute functions

Prompts

Pre-built templates

Sampling

AI model interactions

Meshy AI MCP Server Overview

Meshy AI’s Model Context Protocol (MCP) server bridges the gap between conversational AI assistants and advanced 3D content creation workflows. By exposing Meshy AI’s powerful text‑to‑3D, image‑to‑3D, texture application, and remeshing capabilities through MCP, developers can embed sophisticated 3D generation directly into AI‑driven applications. This eliminates the need for manual API integration and allows assistants to orchestrate complex 3D pipelines with simple, declarative tool calls.

The server offers a rich set of tools that cover the entire 3D asset lifecycle. Creation tools such as and let users generate mesh geometry from natural language or visual references. Texture tools () add material details using textual prompts, while optimizes geometry for real‑time rendering or 3D printing. Each operation is represented as a task that can be queried, listed, and streamed in real time, giving developers full visibility into progress without blocking the AI conversation.

Key capabilities include real‑time streaming of task updates, enabling assistants to present live progress bars or intermediate results. The server also exposes a health check endpoint () and task retrieval resources (), making monitoring and error handling straightforward. A lightweight utility lets users stay informed about API usage limits, preventing unexpected interruptions.

Typical use cases span from game asset pipelines—where a designer can request an object from a prompt and immediately preview it—to educational tools that generate interactive 3D models on demand. In content creation suites, the server can serve as a backend for chat‑based design assistants that guide artists through iterative refinement steps, all while keeping the workflow fully automated and reproducible.

Integration is seamless with any MCP‑compatible client. Developers add a single server configuration to their editor or toolchain, and the assistant can invoke the 3D generation tools as if they were native commands. The server’s modular design means it can be extended with custom tools or combined with other MCP services, making it a versatile component in modern AI‑augmented development environments.