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hedging8563

TokenLab MCP Server

by hedging8563
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JavaScript
Remote

Create image

create_image

Generate images from text prompts with customizable size, style, quality, and more. Supports text-to-image, image-to-image, and image-edit operations.

Instructions

Create image Creates an image given a prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoNumber of images to generate
seedNoSeed for deterministic-compatible image models.
sizeNoImage size. Defaults are model-specific. For gpt-image-2, omit this field or use auto for automatic sizing, or send WIDTHxHEIGHT; custom dimensions must both be multiples of 16, longest edge <= 3840px, long/short ratio <= 3:1, and total pixels between 655,360 and 8,294,400.
userNoEnd-user identifier
asyncNoReturn a task before the final image is ready when the selected model supports public async execution.
modelYesModel to use. Send this explicitly; query GET /v1/models?recommended_for=image for current recommendations.
styleNoOptional model-specific style selector. Only send when the selected model documents support for this parameter.
promptYesImage description
qualityNoImage quality. Defaults and accepted values are model-specific. For gpt-image-2, omit this field or use auto for automatic quality, or send low, medium, or high. Other image families may use provider-specific values.
mask_urlNoOptional mask URL for compatible image operations.
image_urlNoSingle reference image URL for compatible image-to-image models.
operationNoPublic image operation family. Reference-image models use image-to-image with image_url, image_urls, or reference_image_urls.
backgroundNoBackground handling for compatible image flows. For gpt-image-2 generation and edits, accepted values are auto and opaque; transparent is not supported. Other models may support different values.
image_urlsNoReference image URLs for compatible image-to-image models.
moderationNoModeration strictness for compatible image models such as gpt-image-2
resolutionNoResolution selector for compatible image model families.
compressionNoAlias for output_compression when supported by the selected model
aspect_ratioNoAspect-ratio selector for compatible image model families.
expand_promptNoAsk compatible models to expand or enhance the prompt.
output_formatNoOutput image format for compatible image models such as gpt-image-2
negative_promptNoContent to avoid for compatible image models.
response_formatNoResponse formaturl
output_compressionNoOutput compression level from 0 to 100 for compressed formats
reference_image_urlsNoAlias used by compatible reference-image model families.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed6 schema fields changedv0.6.4
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • changedInput schema / properties / background / description
      Previous value: -"Background handling for compatible image generation flows such as gpt-image-2 text-to-image. Not supported for gpt-image-2 image edits."New value: +"Background handling for compatible image flows. For gpt-image-2 generation and edits, accepted values are auto and opaque; transparent is not supported. Other models may support different values."
    • removedInput schema / properties / seed / maximum
      Removed value: -9007199254740991
    • removedInput schema / properties / seed / minimum
      Removed value: --9007199254740991
    • removedInput schema / properties / stream
      Removed value: -{
-  "const": false,
-  "description": "Image streaming is not exposed through MCP tool calls; omit stream or set it to false.",
-  "type": "boolean"
-}
    • changedInput schema / required
      Previous value: -[
-  "prompt",
-  "model"
-]New value: +[
+  "model",
+  "prompt"
+]
  2. Changed5 schema fields changedv0.6.3
    • removedInput schema / properties / quality / default
      Removed value: -"standard"
    • changedInput schema / properties / quality / description
      Previous value: -"Image quality. GPT Image models such as gpt-image-2 use auto/low/medium/high. Other image families may use provider-specific values."New value: +"Image quality. Defaults and accepted values are model-specific. For gpt-image-2, omit this field or use auto for automatic quality, or send low, medium, or high. Other image families may use provider-specific values."
    • removedInput schema / properties / quality / enum
      Removed value: -[
-  "standard",
-  "hd",
-  "auto",
-  "low",
-  "medium",
-  "high"
-]
    • removedInput schema / properties / size / default
      Removed value: -"1024x1024"
    • changedInput schema / properties / size / description
      Previous value: -"Image size. For gpt-image-2, use auto or WIDTHxHEIGHT; custom dimensions must both be multiples of 16, longest edge <= 3840px, long/short ratio <= 3:1, and total pixels between 655,360 and 8,294,400."New value: +"Image size. Defaults are model-specific. For gpt-image-2, omit this field or use auto for automatic sizing, or send WIDTHxHEIGHT; custom dimensions must both be multiples of 16, longest edge <= 3840px, long/short ratio <= 3:1, and total pixels between 655,360 and 8,294,400."
  3. Addedv0.3.1

TDQS

C2.7/5.0
Behavior2/5

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

Annotations are limited (readOnlyHint=false, no destructive hint). Description adds minimal behavioral info: only that it creates an image from a prompt. Does not disclose async capability, model-specific behaviors, or that it can return multiple images. For a mutation tool, more transparency expected.

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

Conciseness3/5

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

Single sentence is concise but wastes words repeating the name. Could be more structured to front-load key info like 'Generates images from prompts with model-specific options.'

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

Completeness1/5

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

Very incomplete for a 24-parameter tool. No mention of return format, async option, model recommendations, or that many parameters are model-specific. Only covers the bare minimum.

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%; description adds no additional meaning beyond 'given a prompt'. Baseline 3 is appropriate as schema already documents parameters.

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?

States verb 'create' and resource 'image' clearly. However, it doesn't distinguish from sibling 'create_image_file' which likely creates a file object rather than returning image data. The description is adequate but not specific about scope.

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs alternatives like edit_image or create_image_file. No context about required model selection or prerequisites.

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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