Multimodal AI

Smart Multi-Image Editing API v3 MCP

Create an edited output from multiple source images using prompt, resolution, and quality controls. Available via REST API or MCP.

CostEst. 139–167 credits / callOnline Test

Smart Multi-Image Editing 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. Combine Product References

Prompt: Combine [reference images] using [supported image model] and [fusion brief]. Preserve the intended product and outfit details.

2. Create Several Alternatives

Prompt: Combine [reference images] using [supported image model] and [fusion brief]. Preserve the intended product and outfit details. Create [number of outputs within this tool’s supported limit] for review, keeping the same source material and brief.

3. Fit The Output To A Placement

Prompt: Combine [reference images] using [supported image model] and [fusion brief]. Preserve the intended product and outfit details. Use [supported resolution] and [supported aspect ratio] for my target placement. Check compatibility with the selected image model.

4. Choose GPT Image Quality

Prompt: Combine [reference images] using [supported image model] and [fusion brief]. Preserve the intended product and outfit details. When using the supported GPT Image provider, use [low, medium or high quality]. Do not apply this provider-specific option to other models.

5. Choose The Editing Route

Prompt: Combine [reference images] using [supported image model] and [fusion brief]. Preserve the intended product and outfit details. Use [economy or stable generation] and choose whether to refine my editing instruction before processing. Preserve my intended change.

6. Apply The Outfit Fusion Edit

Prompt: Combine [reference images] using [supported image model] and [fusion brief]. Preserve the intended product and outfit details. Use the outfit fusion template for this edit, with my supplied material and directions. Review the result before using it publicly.

7. Apply The Outfit Try On Edit

Prompt: Combine [reference images] using [supported image model] and [fusion brief]. Preserve the intended product and outfit details. Use the outfit try on template for this edit, with my supplied material and directions. Review the result before using it publicly.

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/json

Authentication

Use OAuth 2.1 Authorization Code with PKCE and the mcp:tools scope. API keys remain supported as a compatibility option.

Authorization: Bearer nk-xxxxxxxxxxxxxxxxx

Using an API key? Get your key from API Access and include it in the Authorization header shown above.

Call this MCP tool

MCP tool name

nexscope_smart_multi_image_editing_v3

MCP endpoint

https://api.nexscope.ai/mcp

JSON-RPC method

tools/call

Initialize an MCP 2025-11-25 Streamable HTTP session at https://api.nexscope.ai/mcp, then use tools/call.

{
  "jsonrpc": "2.0",
  "id": "smart-multi-image-editing-v3-1",
  "method": "tools/call",
  "params": {
    "name": "nexscope_smart_multi_image_editing_v3",
    "arguments": {
      "aspectRatio": "1:1",
      "imageList": [
        "https://example.com/product.jpg",
        "https://example.com/model-reference.jpg"
      ],
      "needOptimize": true,
      "outputNum": 1,
      "prompt": "combine the product with the model in a clean studio scene",
      "provider": "BANANA_PRO",
      "quality": "medium",
      "resolution": "1K",
      "supplyType": "stable",
      "template": "outfit-fusion"
    }
  }
}

MCP 2025-11-25 · Streamable HTTP

Progress 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": "smart-multi-image-editing-v3-result-1",
  "method": "tools/call",
  "params": {
    "name": "nexscope_media_task_result",
    "arguments": {
      "skillSlug": "smart-multi-image-editing-v3",
      "taskId": "TASK_ID_FROM_THE_GENERATION_RESULT"
    }
  }
}

Arguments

Name	Type	Required	Description
`imageList`	`array`	required	Public image URLs to combine or reference. Provide no more than 6 JPG, JPEG, PNG, or WEBP images; each image must be at most 10 MB and between 800 and 4096 pixels. Example: [ "https://example.com/product.jpg", "https://example.com/model-reference.jpg" ]
`provider`	`string`	required	Image model. Available options `BANANA` `BANANA_2` `BANANA_PRO` `WAN2_7` `QWEN_IMAGE_3_PRO` `SEEDREAM5` `GPT_2_IMAGE` `AIDRAW_EDIT` Example: BANANA_PRO
`prompt`	`string`	optional	Optional fusion instruction, up to 600 characters. Example: combine the product with the model in a clean studio scene
`outputNum`	`integer`	optional	Number of images to generate. Defaults to 1. Example: 1
`resolution`	`string`	optional	Target resolution preset. Example: 1K
`aspectRatio`	`string`	optional	Target aspect ratio. Example: 1:1
`supplyType`	`string`	optional	Generation route. Defaults to stable. Available options `eco` `stable` Example: stable
`needOptimize`	`boolean`	optional	Whether the prompt should be optimized upstream. Example: true
`template`	`string`	optional	Optional fusion template. Available options `outfit-fusion` `outfit-try-on` Example: outfit-fusion
`quality`	`string`	optional	GPT Image quality only. Defaults to medium. Available options `low` `medium` `high` Example: medium

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

Use Smart Multi-Image Editing with the supplied reference material for this brief: combine the product with the model in a clean studio scene

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": "smart-multi-image-editing-v3-example",
  "method": "tools/call",
  "params": {
    "name": "nexscope_smart_multi_image_editing_v3",
    "arguments": {
      "aspectRatio": "1:1",
      "imageList": [
        "https://example.com/product.jpg",
        "https://example.com/model-reference.jpg"
      ],
      "needOptimize": true,
      "outputNum": 1,
      "prompt": "combine the product with the model in a clean studio scene",
      "provider": "BANANA_PRO",
      "resolution": "1K",
      "supplyType": "stable",
      "template": "outfit-fusion"
    }
  }
}

MCP Response Format

{
  "jsonrpc": "2.0",
  "id": "smart-multi-image-editing-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
  }
}

Smart Multi-Image Editing API v3 MCP

Smart Multi-Image Editing API v3 AI Prompts & Use Cases

1. Combine Product References

2. Create Several Alternatives

3. Fit The Output To A Placement

4. Choose GPT Image Quality

5. Choose The Editing Route

6. Apply The Outfit Fusion Edit

7. Apply The Outfit Try On Edit

What You Need to Provide

Connect Your AI Assistant

Authentication

Call this MCP tool

Asynchronous task workflow

Arguments

Response fields

Any of option 1 — requires taskId, status, result

Any of option 1

Any of option 2

Any of option 2

Format Illustration

Illustrative Question

Illustrative Response Explanation

Examples

MCP Request

MCP Response Format

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