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A Practical Guide to Image Editing with GPT Image 2

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When you need to modify an existing image without rebuilding the whole asset from scratch, the hard part is usually control: keeping the composition stable while changing only the parts you asked for. This guide walks through the GPT Image 2 / 2.5 image editing API on Ace Data Cloud. The goal is not to cover every possible creative use case, but to show the practical request shapes you will actually use as a builder: URL-based editing, local image upload, mask-constrained edits, and async callbacks for slower jobs. What you can do The image edits endpoint lets you send an existing image plus an editing instruction, then receive an edited image URL or base64 result depending on response_format . The documented endpoint is: POST https://api.acedata.cloud/openai/images/edits Common use cases include: Changing a product color while preserving the camera angle, lighting, and layout. Replacing a background for a product or profile image. Using up to 16 reference images...
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Getting Started with Flux MCP in Claude Desktop, VS Code, and Cursor

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If you have ever copied prompts out of your editor, pasted them into a separate image tool, waited for a result, and then tried to bring the asset back into your workflow, Flux MCP is a cleaner way to work: it lets your AI client call image-generation and image-editing tools directly from the conversation where you are already building. What you can do The Flux MCP Server from Ace Data Cloud gives an MCP-compatible client a small set of image tools that are practical for day-to-day builder workflows. According to the integration guide, it supports text-to-image generation, image editing from text instructions, multi-model use across Flux Pro, Flux Dev, Flux Schnell, Flux Kontext, and related Flux models, plus task and model queries. In practice, that means you can ask your client to generate a visual concept, revise an existing image, inspect available model options, and check asynchronous task progress without leaving Claude Desktop, VS Code, Cursor, or another MCP-aware envir...
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How to Use NanoBanana MCP in Cursor for Practical Image Editing

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Most image tools are easiest to use when you are already in a browser tab. But when you are writing a README, polishing a product page, or preparing screenshots for a blog post, the place where you actually notice the need for an image edit is often your editor. This guide shows how to wire NanoBanana MCP into Cursor so the editing step can happen inside the same agent workflow where you write and ship. The goal is not to replace a design tool. It is to make small, practical visual tasks easier: cleaning up a screenshot, composing two images, or generating a lightweight illustration while you are still working in the project. What you can do The NanoBanana MCP document describes two main capabilities exposed to Cursor: nanobanana_generate_image for text-to-image generation. nanobanana_edit_image for image editing, including multiple image input. That second point is the useful one for builders. Instead of asking an image model for a completely new asset every time, you c...
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How to Add Flux MCP to Claude Code for Image Generation

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When you are working inside Claude Code, switching to a browser just to generate or edit an image breaks the flow. The Flux MCP setup lets Claude Code call a remote image-generation tool from the same terminal session, so you can keep the surrounding project context in place while producing visual assets. What you can do The Flux MCP guide describes a Claude Code integration for image generation and image editing through Ace Data Cloud. Once configured, Claude Code can call Flux from natural language prompts instead of making you leave the editor. Use flux_generate_image for text-to-image generation. Use flux_edit_image for editing an existing image. Start with fast draft exploration using Flux Dev. Move to Flux Pro when you want more detail and resolution. Use Flux Kontext when you need to change an existing image without regenerating everything. The key idea is not that MCP replaces Claude Code. It adds a callable tool surface to the coding session, so Claude ...
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Настройка Claude Code для командной разработки: единый API-слой без лишней сложности

Claude Code удобен тогда, когда его конфигурация повторяема: локальная машина разработчика, CI-задача и рабочая станция с VS Code используют одинаковые правила доступа, а смена модели не требует переписывать интеграцию. Практичный способ добиться этого — вынести адрес сервиса и секрет в окружение, оставить выбор модели параметром запроса и зафиксировать короткую процедуру проверки. Ниже — рабочая схема для Claude Code и собственных скриптов через Ace Data Cloud. Что подготовить до настройки Сначала откройте русскую версию платформы Ace Data Cloud и создайте приложение в разделе Applications . Там выдается секрет для вызовов. Не помещайте его в репозиторий, тикеты, скриншоты терминала или общий файл конфигурации. Для локальной работы достаточно экспортировать переменную в текущей сессии; для CI лучше применить хранилище секретов конкретной системы. Полезно заранее разделить три сущности: базовый адрес — https://api.acedata.cloud ; секрет — значение, полученное для приложе...
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How to Build Reliable Image Editing Workflows with GPT Image 2

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If your product needs image editing that can preserve composition while changing only the parts you describe, a plain text-to-image call is often too loose. A better pattern is to send the original image, a precise edit instruction, and—when needed—a mask that limits the editable area. What you can do The Ace Data Cloud OpenAI Images Edits endpoint lets you call GPT Image 2 / 2.5 image editing through a single API surface: Edit an image from a URL with a JSON request. Upload a local image with multipart/form-data . Pass one image or multiple reference images; the GPT Image series supports up to 16 reference images. Use a PNG mask with an Alpha channel for local edits when using multipart uploads. Choose between url and b64_json response formats. Use callback_url for longer running tasks. How it works The editing endpoint is POST https://api.acedata.cloud/openai/images/edits . For a URL-based edit, you send JSON with a model , an image URL, a prompt , and...
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Getting Started with Cline in VS Code Using an OpenAI-Compatible Provider

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When you use an AI coding agent inside VS Code, the hard part is often not the prompt—it is getting the provider settings right so the agent can chat, read files, and call tools reliably. What you can do Cline is a VS Code coding agent, and Ace Data Cloud can be configured in Cline through the OpenAI Compatible provider option. The setup is intentionally small: you provide a base URL, an API key, and the model ID made available by your Coding Plan. Once configured, you can use Cline for everyday builder workflows: Start a new task from the Cline panel inside VS Code. Send a minimal verification prompt such as Reply only OK . Ask Cline to read a test file and confirm that the selected model supports tool calling. Review call records later in Ace Data Cloud usage history if you need to debug behavior. How it works Cline's provider configuration has an OpenAI Compatible mode. Instead of using a provider-specific integration, you point Cline at the Ace Data Clo...
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