PicoBerry MCP Server

texture

Apply a new appearance to an existing 3D asset using a text prompt. Creates a revised PBR asset asynchronously, ready for retrieval with wait_for_asset.

Instructions

Re-texture an existing 3D asset (PBR) into a NEW asset (async). Describe the desired look in prompt. Costs credits — see list_models(category='texture'). wait_for_asset → files.model.

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": {
      "asset_id": "<asset_id>"
    },
    "name": "texture"
  }
}

Input Schema

Name	Required	Description	Default
`engine`	No
`prompt`	No
`asset_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 14, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations provided, so description carries full burden. It discloses async nature, credit costs, and how to retrieve output via wait_for_asset. However, it does not state side effects on the original asset (likely non-destructive) or mention any required permissions or rate limits.

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?

The description is two sentences with zero wasted words. It is front-loaded with the core action and efficiently packs async behavior, credit info, and result retrieval into a compact form.

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

Completeness4/5

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

Given 3 parameters, no output schema, and no annotations, the description covers async nature, credit costs, and result retrieval. It omits explanation of the `engine` parameter and could clarify 'PBR' but overall is adequate for the tool's complexity.

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

Parameters3/5

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

Schema coverage is 0%, so description must compensate. It explains the purpose of `prompt` ('Describe the desired look') and implies `asset_id` is the existing asset. However, the `engine` parameter is left undefined, and no default values or options are mentioned.

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 clearly states the verb 'Re-texture', the resource 'existing 3D asset (PBR)', and the outcome 'NEW asset (async)'. It distinguishes from sibling tools like generate_3d_from_image/generate_3d_from_text which create assets from scratch, and animate which focuses on animation.

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 usage cues: 'Describe the desired look in `prompt`', points to list_models for credit info, and specifies wait_for_asset to retrieve the result. It implies when to use (retexturing existing asset) but lacks explicit exclusions or alternatives for cases like generating new textures from scratch.

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

Deploy Server