Image Generation Models
GPT Image 2.5 Flare MCP
Create and edit ecommerce visuals with detailed instruction following, flexible visual styles, world-knowledge grounding. Available via REST API or MCP.
GPT Image 2.5 Flare 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. Generate A Product Image
Prompt: Use GPT Image 2.5 Flare to create an image of [product] in [scene], following [composition and visual style]. Use only the product facts I provide.
2. Create From Product References
Prompt: Use GPT Image 2.5 Flare with [product reference images] to create [new composition]. Preserve the visible product design and avoid adding unsupported features.
3. Prepare Images For A Placement
Prompt: Use GPT Image 2.5 Flare to create an image of [product] in [scene], following [composition and visual style]. Use only the product facts I provide. Use [supported aspect ratio] and [supported resolution] for the intended placement. Keep the requested composition readable at that size.
4. Create A Small Set Of Alternatives
Prompt: Use GPT Image 2.5 Flare to create an image of [product] in [scene], following [composition and visual style]. Use only the product facts I provide. Generate [number of images within the documented limit] for review, using the same product brief. Treat each image as a generated variation.
5. Choose Image Quality
Prompt: Use GPT Image 2.5 Flare to create an image of [product] in [scene], following [composition and visual style]. Use only the product facts I provide. Use [supported image quality level] for this draft. Keep the same creative brief so I can compare output quality.
What You Need to Provide
Provide a written brief; reference images are optional for this model. Follow the image count, file type and size limits in Parameters & Response.
A task receipt is not a finished image. Check the existing task for its terminal result rather than submitting another generation request.
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_gpt_image_2_5_flare_generationhttps://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": "gpt-image-2-5-flare-generation-1",
"method": "tools/call",
"params": {
"name": "nexscope_gpt_image_2_5_flare_generation",
"arguments": {
"aspectRatio": "1:1",
"imageUrls": [],
"outputNum": 1,
"prompt": "Keep the product consistent and generate a clean white-background ecommerce hero image.",
"quality": "medium",
"resolution": "2K"
}
}
}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": "gpt-image-2-5-flare-generation-result-1",
"method": "tools/call",
"params": {
"name": "nexscope_media_task_result",
"arguments": {
"skillSlug": "gpt-image-2-5-flare-generation",
"taskId": "TASK_ID_FROM_THE_GENERATION_RESULT"
}
}
}Arguments
| Name | Type | Required | Description |
|---|---|---|---|
imageUrls | array | optional | Optional public reference image URLs. Omit this field for text-to-image generation, or provide references for image-to-image generation. When supplied, provide 1 to 10 JPG, PNG, or WEBP images; each image must not exceed 20 MB. Example: [] |
prompt | string | required | Generation prompt describing the target image, scene, composition, style, and constraints. Maximum 5000 characters. Example: Keep the product consistent and generate a clean white-background ecommerce hero image. |
outputNum | integer | optional | Number of images to generate. Valid range: 1 to 10; defaults to 1. Example: 1 |
resolution | string | optional | Output resolution. Available options
Example: 2K |
aspectRatio | string | optional | Output aspect ratio. Available options
Example: 1:1 |
quality | string | optional | GPT Image quality. Defaults to medium. Available options
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 GPT Image 2.5 Flare with the supplied reference material for this brief: Keep the product consistent and generate a clean white-background ecommerce hero image.
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": "gpt-image-2-5-flare-generation-example",
"method": "tools/call",
"params": {
"name": "nexscope_gpt_image_2_5_flare_generation",
"arguments": {
"aspectRatio": "1:1",
"imageUrls": [],
"outputNum": 1,
"prompt": "Keep the product consistent and generate a clean white-background ecommerce hero image.",
"quality": "medium",
"resolution": "2K"
}
}
}MCP Response Format
{
"jsonrpc": "2.0",
"id": "gpt-image-2-5-flare-generation-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
}
}