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codex-openai-image-mcp

codex-openai-image-mcp

by meet30997

Generate matching set

generate_set

Generates several images that share one style, such as icon sets, stickers, badges, or character portraits, saving each item as a named file in a folder and returning paths and previews.

Instructions

Generate several different images that share one style, e.g. a set of icons, stickers, badges, character portraits or story illustrations. Each item gets its own file, named after the item, in one folder. Returns paths and previews.

Input Schema

NameRequiredDescriptionDefault
sizeNoWidth x height in px for every image, e.g. "1024x1024".1024x1024
itemsYesThe images to make, one per item.
styleYesThe look every image shares: medium, palette, rendering, lighting, framing, background.
folderNoFolder for the set, relative to the output folder. Defaults to a slug of the style.
referencesNoExisting images whose style the whole set should match (inside the working folder).
transparentNoAsk for transparent backgrounds.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A3.8/5.0
Behavior4/5

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

Annotations only declare the safety profile (not read-only, open-world, non-destructive), so the description usefully adds that each item produces its own file named after the item, all in one folder, and that paths and previews are returned. It stops short of stating overwrite/conflict behavior for an existing folder or any rate/cost limits, which matters given openWorldHint.

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 short sentences, front-loaded with the core purpose, followed by output layout and return values. No filler or repetition of schema details.

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?

It covers what the tool produces and what it returns (paths and previews), which compensates for the absent output schema on a 6-parameter tool. Gaps remain around folder collision behavior and whether style/items have any content restrictions, but nothing essential to invoking it is missing.

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 100%, so the schema already documents style, items, size, folder, references, and transparent. The description contributes only the linkage that item names become file names and that everything lands in one folder — helpful but marginal, so baseline 3 applies.

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

Purpose4/5

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

Specific verb (generate) plus resource (several images sharing one style), reinforced by concrete examples (icons, stickers, badges, portraits, story illustrations). It implicitly separates itself from generate_image by emphasizing 'several' and 'share one style,' but never names the sibling tools, so the differentiation is inferred rather than stated.

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

Usage Guidelines3/5

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

The example list gives a reasonable sense of when a matched set is appropriate, but there is no explicit guidance on when to prefer generate_image for a single image or edit_image for modifying existing art. No prerequisites, exclusions, or cost/batching trade-offs are stated.

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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