AI Integration

Meshy exposes two channels for AI agents and coding assistants: the Meshy MCP server for tool-calling, and llms.txt / llms-full.txt for docs ingestion.

If you are integrating Meshy from Claude Code, Cursor, Windsurf, Codex, or any other MCP-compatible tool, install the MCP server below. If you are integrating from a plain chat agent with no MCP support, point it at https://docs.meshy.ai/llms.txt instead.

What is MCP

The Model Context Protocol (MCP) is an open standard that lets AI assistants call external tools and retrieve structured context. The Meshy MCP server wraps the Meshy REST API as a set of tools your agent can invoke — generate a model, check a task, download the result — without hand-writing HTTP code.

The MCP server is open source and published on npm as @meshy-ai/meshy-mcp-server. Source: github.com/meshy-dev/meshy-mcp-server.

You need a Meshy API key. Create one at https://www.meshy.ai/settings/api. The MCP server reads it from the MESHY_API_KEY environment variable.

Quick Install

# Detects installed AI clients and configures Meshy for each
npx add-mcp meshy -- npx -y @meshy-ai/meshy-mcp-server -e MESHY_API_KEY=msy_YOUR_API_KEY

Available Tools

The MCP server exposes the Meshy REST API as tools, grouped by capability.

3D Generation

  • meshy_text_to_3d — create a 3D model from a text prompt
  • meshy_image_to_3d — create a 3D model from one image
  • meshy_multi_image_to_3d — create a 3D model from multiple images of the same object
  • meshy_text_to_3d_refine — add texture to a preview mesh

Post-Processing

  • meshy_remesh — change topology and/or polycount of an existing model
  • meshy_retexture — apply a new texture to an existing model
  • meshy_rig — add a skeleton to a 3D humanoid character
  • meshy_animate — apply an animation to a rigged character

Image Generation

  • meshy_text_to_image — 2D image from text
  • meshy_image_to_image — 2D image from a reference image

Task Management

  • meshy_get_task_status — check task status and download URLs
  • meshy_list_tasks — list recent tasks, optionally filtered by type/status
  • meshy_cancel_task — cancel a pending or in-progress task
  • meshy_download_model — fetch a completed model file and save locally

Workspace

  • meshy_list_models — list all models in the authenticated user's workspace

3D Printing

  • meshy_send_to_slicer — detect installed slicers and launch the model in one (runs locally on your machine; no Meshy API call)
  • meshy_analyze_printability — currently returns a manual print-readiness checklist (wall thickness, overhangs, manifold mesh, etc.). Will be upgraded to automated analysis once the Meshy printability API is available.
  • meshy_process_multicolor — convert a textured model into a multi-color 3MF file for printing

Account

  • meshy_check_balance — query remaining credits

Tool names and behaviors may evolve. The authoritative list lives in the MCP server source.

Example Prompts

Drop these into your MCP-enabled chat as a starting point.

Generate a 3D fox from the prompt "a cartoon fox sitting", preview it, then
texture it with PBR maps. Download the final GLB to ./outputs.

Take the image at https://example.com/sculpture.jpg and convert it into a
riggable 3D character. Use `should_remesh: true` and 50k target polycount.

What's my current Meshy credit balance?

List my last 10 successful text-to-3d tasks and download the top 3 as GLB
into ./downloads/.

llms.txt and llms-full.txt

If your agent doesn't support MCP, or you want to ingest the Meshy docs into a prompt directly, point it at our plain-text surfaces:

  • llms.txt — compact index + integration instructions (the correct async-polling pattern, auth rules, rate limits, model choice, common mistakes).
  • llms-full.txt — every API page concatenated in a single file for single-fetch ingestion.
  • Per-page Markdown: append .md to any endpoint URL. Example: https://docs.meshy.ai/api/text-to-3d.md.

All three are regenerated every time the docs site builds, so they never drift from the HTML docs.

FAQ

Is the MCP server stateless?

Yes. Your MESHY_API_KEY is used per request and never persisted on the server side.

Does MCP cost the same as the REST API?

Yes — every MCP tool call maps to a single REST call and consumes credits at the exact same rate. See Pricing for the full matrix.

What are the rate limits?

The MCP server shares the same rate-limit plane as the REST API. See Rate Limits for per-tier limits.

What Meshy data can the MCP access?

Only what the MESHY_API_KEY can access via REST. Scopes and permissions are identical.

How do I report issues?

File an issue at github.com/meshy-dev/meshy-mcp-server.