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Meshy MCP Server

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by meshy-dev

List Finished 3D Models

meshy_list_models
Read-onlyIdempotent

List finished 3D models by date, showing task IDs, types, and downloadable formats; defaults to image-to-3d results, with task_types to include more.

Instructions

List your finished 3D models (not AI models), newest first, each with its task_id, task_type and formats ready for meshy_download_model. Queries only image-to-3d by default (one request); pass task_types to widen. meshy_list_tasks lists tasks of any status instead, images included.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoResults per page, 1–100
filterNoDeprecated; ignored.
offsetNoResults to skip
task_typesNoModel task types to list (default ["image-to-3d"], one request). Pass several, e.g. ["text-to-3d", "image-to-3d", "multi-image-to-3d"], to widen; each type is one more request.
workspace_idNoDeprecated; ignored.
response_formatNomarkdown (default) or jsonmarkdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.4

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description adds genuinely useful behavioral context beyond that: newest-first ordering, the fields returned (task_id, task_type, formats), and the request-cost implication that each task_type is 'one more request.'

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the core purpose, then the default/widening behavior, then the sibling disambiguation. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the return-value burden and does so by naming the returned fields and their downstream use (ready for meshy_download_model). Routing, defaults, and pagination (in schema) are all covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds contextual meaning: the image-to-3d default and the request-cost consequence of widening task_types. It slightly exceeds the schema text by tying the parameter to an operational cost model.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (List) and resource (finished 3D models), adds scope clarification ('not AI models'), and distinguishes itself from meshy_list_tasks by name. An agent can route between the two list tools without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names the alternative (meshy_list_tasks) and the condition that selects it ('tasks of any status instead, images included'). Also states the default query behavior and how to widen it via task_types, leaving little to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.