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zimage-mcp

zimage-mcp

by sjemmeh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

generate_image

Generate web-dev images from text prompts with customizable size, multiple variants, and seed control. Saves to output path.

Instructions

Generate web-dev image(s) with Z-Image Turbo and save to output_path.

size: one of square|landscape|portrait|hero|wide|og|mobile, or pass width+height for exact pixels (image is generated at the nearest valid size then resized/cropped). n: 1-4 variants (paths get _1,_2,... ); seeds are base_seed, base_seed+1, ... Returns {images, seed, gen_size, output_size, seconds}.

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": {
      "prompt": "<prompt>",
      "output_path": "<output_path>"
    },
    "name": "generate_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
nNo
seedNo
sizeNosquare
stepsNo
widthNo
heightNo
promptYes
negativeNo
output_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations are provided, so the description carries full burden. It explains generation behavior (resizing/cropping to nearest valid size, multiple variants using seeds, saving to output_path, return format). It does not mention overwrite behavior, auth requirements, or computational cost, but covers essential behavioral traits.

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 compact and well-structured: a lead sentence defining the action, followed by concise bullet-like explanations for key parameters (size, n, seeds, returns). Every sentence adds value, no redundancy.

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 no output schema, the description includes return format. It covers size flexibility, multi-image generation, and output saving. However, it lacks details on step parameter semantics, negative prompt effects, and potential edge cases (e.g., path conflicts). Still, it is largely complete for an AI agent.

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 0%, so description compensates by explaining size (named presets or width+height), n and seed inference, and the return object. It does not detail steps or negative prompt semantics, but most parameters are covered sufficiently for usage.

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 explicitly states 'Generate web-dev image(s) with Z-Image Turbo and save to output_path', clearly identifying the verb (generate), resource (web-dev images), and output. Sibling tools (health, list_presets) are completely unrelated, so no confusion.

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 does not provide explicit when/when-not guidance, but the purpose is distinct from siblings, and the parameter explanations implicitly define usage context. It would benefit from stating 'Use this to generate images, not for health checks or listing presets'.

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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