GPT Image MCP Server

text_to_image

Create a GPT Image task on RunAPI from a text prompt to generate images, returning a task ID, status, and output URLs.

Instructions

Create a GPT Image task on RunAPI (text to image). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema

Name	Required	Description
`wait`	No	Poll until the task reaches a terminal status.
`model`	No	RunAPI model slug for this model line.
`prompt`	Yes	Declared type: string.
`quality`	Yes	Declared type: string. Known values: "medium", "high".
`timeout_ms`	No
`aspect_ratio`	Yes	Declared type: string. Known values: "1:1", "2:3", "3:2".
`callback_url`	No	Declared type: string.
`poll_interval_ms`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed10 schema fields changedv0.2.0Oct 5, 2026
- changedInput schema / additionalProperties
```
Previous value: -falseNew value: +{}
```
- addedInput schema / properties / aspect_ratio / description
```
Added value: +"Declared type: string. Known values: \"1:1\", \"2:3\", \"3:2\"."
```
- removedInput schema / properties / aspect_ratio / enum
```
Removed value: -[
-  "1:1",
-  "2:3",
-  "3:2"
-]
```
- addedInput schema / properties / callback_url / description
```
Added value: +"Declared type: string."
```
- removedInput schema / properties / model / enum
```
Removed value: -[
-  "gpt-image-1.5"
-]
```
- addedInput schema / properties / poll_interval_ms / maximum
```
Added value: +9007199254740991
```
- addedInput schema / properties / prompt / description
```
Added value: +"Declared type: string."
```
- addedInput schema / properties / quality / description
```
Added value: +"Declared type: string. Known values: \"medium\", \"high\"."
```
- removedInput schema / properties / quality / enum
```
Removed value: -[
-  "medium",
-  "high"
-]
```
- addedInput schema / properties / timeout_ms / maximum
```
Added value: +9007199254740991
```

Changed3 schema fields changedv0.1.8Aug 5, 2026

addedInput schema / properties / callback_url
```
Added value: +{
+  "type": "string"
+}
```
addedInput schema / properties / prompt / type
```
Added value: +"string"
```

changedInput schema / required

Previous value: -[
-  "quality",
-  "aspect_ratio"
-]New value: +[
+  "prompt",
+  "aspect_ratio",
+  "quality"
+]

First observedv0.1.0Jun 24, 2026

TDQS

B3.2/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose a meaningful behavioral trait: this is an async task-creation call that returns an id, status, and output URLs rather than the image itself. However it says nothing about authentication needs, cost implications, or how the 'wait' polling flag changes behavior.

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?

Two tightly written sentences with the core action and the return shape front-loaded. There is no padding, though it is arguably too terse to cover the tool's async behavior.

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

Completeness3/5

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

For an 8-parameter async image-generation tool with no output schema, the description does state return values, which compensates somewhat. But it omits the polling/wait semantics, callback behavior, and routing guidance to sibling tools like get_task, leaving a partially complete picture.

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 description coverage is 75%, and the description adds no parameter-level detail at all. The schema already documents wait, model, quality values, and aspect_ratio values; the description does not compensate for the undocumented prompt, timeout_ms, poll_interval_ms, or callback_url. Baseline 3 given the reasonably high schema coverage.

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 a specific verb and resource: 'Create a GPT Image task on RunAPI (text to image).' The parenthetical distinguishes it from the sibling edit_image, which is the nearest alternative. It stops short of naming siblings explicitly, so it is clear but not fully differentiated.

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?

There is no statement of when to use this tool versus edit_image or get_task, nor any prerequisites. The mention that it 'Returns a task id' only weakly implies that get_task is the follow-up call. An agent must infer the async workflow.

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

Deploy Server

text_to_image

Instructions

Input Schema

Schema Changelog

TDQS

Other Tools