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How to Use NanoBanana MCP in Claude Code for Image Editing Workflows

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When a coding task needs a visual asset, the slow part is often leaving the terminal: open a browser, upload references, write a prompt, download the result, and then return to the repo. NanoBanana MCP lets Claude Code call image generation and image editing tools directly from the same terminal workflow. What you can do The Ace Data Cloud NanoBanana MCP documentation focuses on two practical capabilities inside Claude Code: nanobanana_generate_image for text-to-image generation. nanobanana_edit_image for image editing, including workflows that pass multiple image URLs. That makes it a good fit for builder tasks where the image is part of the product work rather than a separate design session: README illustrations, 404 page artwork, product mockups, background cleanup, or combining an object from one image with the scene from another. How it works Claude Code supports MCP servers over HTTP. The NanoBanana server is exposed at https://nanobanana.mcp.acedata.cloud/...
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A Practical Guide to Using Ace Data Cloud MCP in Cursor

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Modern coding work rarely stops at code: you may finish a README, then need a cover image, fresh research, short links for release notes, or media assets for a tutorial without leaving your editor. What you can do Ace Data Cloud exposes several managed remote MCP Servers that Cursor can call from Composer or Chat. The documented services cover practical builder tasks rather than a single narrow API: Suno for music, Flux and Seedream for image generation and editing, NanoBanana for Gemini-driven image editing such as product scene changes and virtual fitting, Luma , Veo , and Seedance for video work, Serp for Google search, and ShortURL for link shortening. The useful part is not that these tools exist separately. It is that Cursor can keep the workflow inside the editor. You can ask it to research a topic, draft an outline, generate a visual, and prepare links while it still understands the files you are editing. How it works MCP, or Model Context Protocol, lets an A...
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Единый API и X402: практическая схема расчётов для мультимодельного приложения

У мультимодельного приложения обычно две независимые задачи: выбрать подходящую модель и сделать расчёты за вызовы наблюдаемыми. Первая решается через единый API-контракт, вторая — через ограничение расходов, журналирование и понятный способ оплаты. В этой статье разберём практический вариант для Ace Data Cloud: обычный API-токен для сервисов и механизм X402 для сценариев оплаты по запросу. Начать стоит с русской страницы платформы , затем открыть список приложений . Там создают приложение, получают учётные данные и задают границы доступа. Справочные материалы и актуальные параметры моделей находятся в разделе документации . Во всех примерах ниже базовый адрес один: https://api.acedata.cloud . Два пути расчётов и один интерфейс вызова Для регулярного серверного сервиса удобен токен приложения: сначала пополняется баланс, затем каждый вызов списывается из него по правилам выбранной модели. Такой вариант хорошо сочетается с лимитами ключей, метриками и разделением окружений. Для отд...
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How to Build a Practical Image Generation and Editing Flow with the Nano Banana Images API

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If you are building an app that needs both text-to-image generation and reference-based image editing, the awkward part is often not the model prompt. It is designing one API flow that handles creation, edits, retries, result tracking, and user-facing errors without special cases everywhere. The Nano Banana Images API gives you a single endpoint for two related jobs: generating images from prompts and editing existing images with one or more references. This guide walks through a small builder-oriented integration pattern: a minimal request path, an edit path for reference images, and a callback path for production jobs. What you can do The documented interface supports two actions on the same endpoint: generate : create images from a text prompt . edit : edit or combine supplied images using image_urls plus a text prompt . The base URL is https://api.acedata.cloud , and the endpoint is POST /nano-banana/images . Requests use JSON, with authorization: Bearer {token} in ...
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How to Use Ace Data Cloud SDK with X402 Payments

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Ace Data Cloud supports an X402 payment flow that lets the SDK pay for a request after the server responds with 402 Payment Required . Instead of providing an API token, configure a payment handler. The handler signs the server-provided payment envelope locally, and the SDK retries the original request with a PAYMENT-SIGNATURE header. Understand the X402 request flow The flow begins when a request such as /openai/v1/chat/completions is sent without an Authorization header. The server returns 402 Payment Required and an accepts array. The SDK calls your local payment hook with: paymentHandler({ url, method, body, accepts }) Your handler returns headers containing PAYMENT-SIGNATURE . The SDK then resends the original request with that header. After verification and settlement, the server returns the normal 200 business response. The payment envelope includes fields such as x402Version: 2 , an accepted scheme and network, and a payload. An example accepted value uses scheme: ...
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How to Use NanoBanana MCP from Claude Code for Image Editing Workflows

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If your coding agent can already read files, run commands, and help you refactor code, the next useful step is letting it produce the visual assets that usually interrupt your flow: README screenshots, product mockups, 404 illustrations, and small image edits for docs or release notes. What you can do The NanoBanana MCP setup described in the Ace Data Cloud documentation connects Claude Code to a managed MCP server for image generation and image editing. The interesting part is not only text-to-image. The documented workflow emphasizes image understanding: you can provide multiple image URLs and ask the model to combine, reposition, or clean up elements in a way that respects the scene. Once configured, Claude Code can call two documented tools: nanobanana_generate_image for text-to-image generation. nanobanana_edit_image for image editing, including multiple image inputs. That makes the integration practical for builder workflows where the agent already has project con...
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Getting Started with Nano Banana MCP for Image Generation in Your IDE

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If your AI assistant can write code but cannot create or edit the image assets your project needs, you end up leaving the IDE, opening another tool, copying prompts around, and manually downloading files. Nano Banana MCP is a practical way to keep that workflow inside an AI client such as Claude Desktop, VS Code, or Cursor. The idea is simple: install an MCP server, provide an Ace Data Cloud API token through an environment variable, and let your assistant call image tools from the conversation. The documented server is mcp-nanobanana-pro , and it exposes tools for generating, editing, combining, and checking image tasks. What you can do The Nano Banana MCP server is built around image work that developers and product builders often need while prototyping: Generate images from text prompts , for example a watercolor landscape, an illustration, or a product visual. Edit existing images or combine multiple images into a new result. Run virtual try-on workflows , such ...
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