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Thrixel MCP Server

Thrixel MCP Server

Official
by thrixel
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Python
Remote

Retexture a 3D model

thrixel_retexture_model

Generate new textures for a completed 3D model without altering its geometry. Use a reference image to restyle multiple assets consistently, costing 40 cubes per model.

Instructions

Generate fresh textures for a model without touching its geometry. Costs 40 cubes.

This is the cheap way to restyle: to make a whole set of assets cyberpunk, retexture each one against the same reference image rather than regenerating them. Pass the same reference_image_id every time to keep the set consistent - reusing an image is not re-charged.

Works on any completed model, not just detailed ones. To restyle only some parts, name them in apply_to_node_names.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "submission_id": "<submission_id>"
    },
    "name": "thrixel_retexture_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
destNo
seedNo
waitNo
promptNo
project_idNo
texture_sizeNo
submission_idYes
reference_image_idNo
apply_to_node_namesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.6/5.0
Behavior3/5

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

Without annotations, the description carries the full burden. It discloses that the tool costs 40 cubes, does not modify geometry, works on any completed model, and allows selective restyling. However, it misses key behaviors: whether the operation is asynchronous (though wait parameter exists), whether it creates a new model or updates in-place, and what happens on failure. These gaps lower the score.

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

Conciseness4/5

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

The description is efficient: 4 sentences that quickly convey purpose, cost, use case, and parameter tips. It is front-loaded with the main action. However, the sentence about reusing an image could be more direct, and the 'cyberpunk' example is slightly verbose. Still, it wastes very little space.

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

Completeness2/5

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

Given the tool's complexity (9 parameters, no annotations, no output schema), the description is far from complete. It does not describe return values, error scenarios, or the role of most parameters. An agent would lack critical information to invoke the tool safely and correctly.

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

Parameters2/5

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

The input schema has 9 parameters with 0% schema description coverage, so the description must explain them. It only explains reference_image_id and apply_to_node_names, leaving 7 other parameters (submission_id, dest, seed, wait, prompt, project_id, texture_size) completely unexplained. This is insufficient for an agent to use the tool correctly without guessing.

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?

The description starts with a clear verb+resource: 'Generate fresh textures for a model without touching its geometry.' It distinguishes itself from siblings like thrixel_create_model or thrixel_sculpt_model by explicitly focusing on retexturing and calling it the 'cheap way to restyle', contrasting with regeneration. This makes the purpose highly specific and distinct.

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

Usage Guidelines4/5

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

The description provides useful guidance: it recommends using this tool for cheap restyling, suggests passing the same reference_image_id for consistency, notes that reusing an image is not recharged, mentions that it works on any completed model, and explains how to restyle only some parts using apply_to_node_names. However, it does not explicitly state when not to use this tool or compare it directly to other siblings like thrixel_edit_model, which would make it a 5.

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

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