Multimodal AI
AI Apparel Image Set & Photography API v3 MCP
Create apparel ecommerce image sets from clothing images with optional model and scene references. Available via REST API or MCP.
AI Apparel Image Set & Photography API v3 AI Prompts & Use Cases
After connecting this MCP tool to your AI assistant, you can ask the questions below. Replace bracketed placeholders with your own inputs and use the supported values in Arguments.
New to Nexscope MCP? Follow the connection guide, then use the prompts below. The Integration and Parameters & Response tabs contain the connection steps, call example, and technical reference.
1. Create A Marketing Image Set
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims.
2. Build A Brief From Product Images
Prompt: Extract visible selling points from [reference images] and create [requested apparel image types and counts]. Keep uncertain attributes out of the copy.
3. Create Brand-Consistent Layouts
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims. Follow [brand colors], [font style], [sales region], [language], [platform] and [additional brand directions]. Include text only when requested.
4. Prepare A+ Content
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims. Create [standard or premium A+ layouts], optionally including phone layouts, in [supported A+ aspect ratio]. Use [saved A+ styles or a custom layout brief] and [saved selling-point styles or custom callouts].
5. Screen Marketing Copy
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims. Apply my [sensitive-word library] and [replacement-word library] to the generated copy while retaining the verified product facts.
6. Direct The Model And Scene
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims. Use [model reference] and [scene reference] with [model and scene brief]. Choose whether to match the scene closely or allow a looser interpretation.
7. Fit The Output To A Placement
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims. Use [supported resolution] and [supported aspect ratio] for my target placement. Check compatibility with the selected image model.
8. Choose An Image Model
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims. Use [supported image or analysis model] for this task, keeping the same references and creative brief.
9. Choose GPT Image Quality
Prompt: Create a apparel image set from [reference images] using [verified selling points]. Produce [requested image types and counts] and do not invent product claims. When using the supported GPT Image provider, use [low, medium or high quality]. Do not apply this provider-specific option to other models.
What You Need to Provide
Provide assets you may use and that meet this tool’s documented file, dimension and count limits.
A pending task is not a completed image, video or text result. Retrieve the existing task rather than submitting a duplicate.
Step 1 · Connect
Connect Your AI Assistant
Connect a compatible MCP client to Nexscope, then select this tool from your assistant. Use the connection settings in your client to complete authentication.
POST https://api.nexscope.ai/mcp
MCP-Protocol-Version: 2025-11-25
Content-Type: application/jsonAuthentication
Use OAuth 2.1 Authorization Code with PKCE and the mcp:tools scope. API keys remain supported as a compatibility option.
Authorization: Bearer nk-xxxxxxxxxxxxxxxxxUsing an API key? Get your key from API Access and include it in the Authorization header shown above.
Call this MCP tool
nexscope_ai_apparel_image_set_photography_v3https://api.nexscope.ai/mcptools/callInitialize an MCP 2025-11-25 Streamable HTTP session at https://api.nexscope.ai/mcp, then use tools/call.
{
"jsonrpc": "2.0",
"id": "ai-apparel-image-set-photography-v3-1",
"method": "tools/call",
"params": {
"name": "nexscope_ai_apparel_image_set_photography_v3",
"arguments": {
"aPlusAspectRatio": "1:1",
"aPlusHasPhone": false,
"aPlusNum": 0,
"aPlusProNum": 0,
"aPlusStyles": [
{
"id": 1
},
{
"prompt": "clean editorial layout"
}
],
"aspectRatio": "1:1",
"brandKey": "{\"brandColor\":\"#0775FA\",\"fontStyle\":\"sans serif\",\"salesRegion\":\"North America\",\"language\":\"English\",\"platform\":\"Amazon\"}",
"imageList": [
"https://example.com/product.jpg"
],
"insTypeNum": 0,
"isExactScene": true,
"isExtractPrePoint": false,
"modelAndSceneInfo": "{\"model\":\"female adult\",\"scene\":\"studio\"}",
"modelImageUrl": "https://example.com/model-reference.jpg",
"modelTypeNum": 0,
"noText": false,
"pointStyles": [
{
"id": 2
},
{
"prompt": "minimal feature callouts"
}
],
"provider": "BANANA_2",
"quality": "medium",
"replaceLibraryId": 1002,
"resolution": "2K",
"sceneImageUrl": "https://example.com/scene.jpg",
"sellerPoint": "Lightweight breathable summer dress",
"sellerTypeNum": 0,
"sensitiveLibraryId": 1001,
"sizeTypeNum": 0,
"whiteTypeNum": 0
}
}
}MCP 2025-11-25 · Streamable HTTPProgress is delivered on the original POST SSE response. GET SSE carries notifications; reconnecting must query existing asynchronous work rather than submit again.
Asynchronous task workflow
- 1. Create once
Keep the returned taskId.
- 2. Query with backoff
Use nexscope_media_task_result after 5 seconds, then 10, 20, and 30 seconds.
- 3. Use final result
Stop at success, failure, or timeout.
{
"jsonrpc": "2.0",
"id": "ai-apparel-image-set-photography-v3-result-1",
"method": "tools/call",
"params": {
"name": "nexscope_media_task_result",
"arguments": {
"skillSlug": "ai-apparel-image-set-photography-v3",
"taskId": "TASK_ID_FROM_THE_GENERATION_RESULT"
}
}
}Arguments
| Name | Type | Required | Description |
|---|---|---|---|
imageList | array | required | Public apparel image URLs. Provide no more than 5 JPG, JPEG, PNG, or WEBP images; each image must be at most 10 MB and between 384 and 4096 pixels. Example: [
"https://example.com/product.jpg"
] |
provider | string | optional | Image model. Defaults to BANANA_2. Available options
Example: BANANA_2 |
sellerPoint | string | optional | Product selling points, up to 2500 characters. Required when isExtractPrePoint is false. Example: Lightweight breathable summer dress |
isExtractPrePoint | boolean | optional | Whether to automatically extract selling points. Defaults to false. When false, sellerPoint is required. Example: false |
resolution | string | optional | Target resolution supported by the selected provider. Example: 2K |
aspectRatio | string | optional | Target aspect ratio. Example: 1:1 |
noText | boolean | optional | Whether generated images should avoid text. Example: false |
brandKey | string | optional | Optional brand information serialized as a JSON string. Supported keys: brandColor, fontStyle, salesRegion, language, platform, customSettings. Example: {"brandColor":"#0775FA","fontStyle":"sans serif","salesRegion":"North America","language":"English","platform":"Amazon"} |
quality | string | optional | GPT Image quality only. Available options
Example: medium |
sensitiveLibraryId | integer | optional | Optional sensitive-word library ID used to screen generated copy. Example: 1001 |
replaceLibraryId | integer | optional | Optional replacement-word library ID used to rewrite generated copy. Example: 1002 |
modelImageUrl | string | optional | Optional model reference image URL. Example: https://example.com/model-reference.jpg |
sceneImageUrl | string | optional | Optional scene reference image URL. Example: https://example.com/scene.jpg |
isExactScene | boolean | optional | Whether to match the provided scene closely. Defaults to true. Example: true |
modelAndSceneInfo | string | optional | Model and scene information serialized as a JSON string or concise structured text. Example: {"model":"female adult","scene":"studio"} |
aPlusNum | integer | optional | Number of standard A+ images, from 0 to 12. Defaults to 0. Example: 0 |
aPlusProNum | integer | optional | Number of premium A+ images, from 0 to 12. Defaults to 0. Example: 0 |
aPlusHasPhone | boolean | optional | Whether A+ output includes phone display layouts. Example: false |
aPlusAspectRatio | string | optional | A+ output aspect ratio. Available options
Example: 1:1 |
modelTypeNum | integer | optional | Number of model images, from 0 to 12. Defaults to 0. Example: 0 |
insTypeNum | integer | optional | Number of social-style images, from 0 to 12. Defaults to 0. Example: 0 |
sellerTypeNum | integer | optional | Number of selling-point images, from 0 to 12. Defaults to 0. Example: 0 |
sizeTypeNum | integer | optional | Number of size-information images, from 0 to 12. Defaults to 0. Example: 0 |
whiteTypeNum | integer | optional | Number of white-background images, from 0 to 12. Defaults to 0. Example: 0 |
aPlusStyles | array | optional | Optional A+ style entries. Each item may contain a saved style id or a custom prompt. Example: [
{
"id": 1
},
{
"prompt": "clean editorial layout"
}
] |
pointStyles | array | optional | Optional selling-point style entries. Each item may contain a saved style id or a custom prompt. Example: [
{
"id": 2
},
{
"prompt": "minimal feature callouts"
}
] |
Response fields
Treat structuredContent as the programmatic API response payload.
| Name | Type | Required | Description |
|---|---|---|---|
code | integer | required | 0 means accepted or successful; nonzero is a platform error. |
cost | string | required | Elapsed milliseconds, never credits; -1 outside web requests. |
data | any | required | Data value used by this API operation. |
msg | string | null | required | Msg value used by this API operation. |
time | string | required | Server local time: yyyy-MM-dd HH:mm:ss. |
traceId | string | null | required | Trace id value used by this API operation. |
ts | string | required | Epoch milliseconds. |
Any of option 1 — requires taskId, status, result
| Name | Type | Required | Description |
|---|---|---|---|
data | object | required | Data value used by this API operation. |
data.result | any | required | Completed generation output retained from the task result. Fields vary by capability; generated resources use Nexscope-hosted URLs and any count represents charged Nexscope credits. This is the business output, not a task creation receipt. |
data.status | string | required | Status value used by this API operation. Allowed: PENDING, RUNNING, SUCCEEDED, FAILED, TIMEOUT |
data.taskId | string | required | Task id value used by this API operation. |
Any of option 1
| Name | Type | Required | Description |
|---|---|---|---|
data.result | object | required | Completed generation output retained from the task result. Fields vary by capability; generated resources use Nexscope-hosted URLs and any count represents charged Nexscope credits. This is the business output, not a task creation receipt. |
Any of option 2
| Name | Type | Required | Description |
|---|---|---|---|
data.result | null | required | Completed generation output retained from the task result. Fields vary by capability; generated resources use Nexscope-hosted URLs and any count represents charged Nexscope credits. This is the business output, not a task creation receipt. |
Any of option 2
| Name | Type | Required | Description |
|---|---|---|---|
data | null | required | Data value used by this API operation. |
Format Illustration
Illustrative example with fictional data, not a live tool call.
Illustrative Question
Create one selling-point image and one white-background image from my product photo at 2K in a square format. Use this product brief: Lightweight breathable summer dress.
Illustrative Response Explanation
The illustrative request has been accepted as task example-task and is PENDING. No completed output is available yet. Keep this task ID and check its result; do not submit the same request again just because processing has not finished.
About this sample: Illustrative format example with fictional values, not a live tool call. Replace example inputs with your own permitted assets or public identifiers.
Published sample data is not available for this page. A format illustration or workflow guide is not a substitute for a published result.
View the MCP Request & Response Format
Examples
Illustrative example with fictional data, not a live tool call.
The JSON-RPC envelope below illustrates how the shown arguments and payload fit into MCP. It is not captured network traffic or proof of a successful call. Workflow-only examples do not include a result.
MCP Request
{
"jsonrpc": "2.0",
"id": "ai-apparel-image-set-photography-v3-example",
"method": "tools/call",
"params": {
"name": "nexscope_ai_apparel_image_set_photography_v3",
"arguments": {
"aspectRatio": "1:1",
"imageList": [
"https://example.com/product.jpg"
],
"provider": "BANANA_2",
"resolution": "2K",
"sellerPoint": "Lightweight breathable summer dress",
"sellerTypeNum": 1,
"whiteTypeNum": 1
}
}
}MCP Response Format
{
"jsonrpc": "2.0",
"id": "ai-apparel-image-set-photography-v3-example",
"result": {
"content": [
{
"type": "text",
"text": "{\"code\":0,\"cost\":\"-1\",\"data\":{\"taskId\":\"example-task\",\"status\":\"PENDING\",\"result\":null},\"msg\":null,\"time\":\"2026-01-01 00:00:00\",\"traceId\":null,\"ts\":\"0\"}"
}
],
"structuredContent": {
"code": 0,
"cost": "-1",
"data": {
"taskId": "example-task",
"status": "PENDING",
"result": null
},
"msg": null,
"time": "2026-01-01 00:00:00",
"traceId": null,
"ts": "0"
},
"isError": false
}
}