AceDataCloud

If your image workflow already starts in an AI chat or coding editor, switching tabs to a separate image tool can break the flow. The Nano Banana MCP Server lets you keep that workflow inside clients such as Claude Desktop, VS Code, and Cursor by exposing image generation and editing as MCP tools. What you can do The Nano Banana MCP Server is documented as a bridge between MCP-compatible AI clients and Ace Data Cloud's Nano Banana image capabilities. Once configured, the client can call a small set of tools directly from the conversation or editor context. Generate images from text prompts with nanobanana_generate_image . Edit or combine existing images with nanobanana_edit_image . Try visual workflows such as virtual try-on and product placement, where an existing person, garment, or product image is part of the task. Track asynchronous work with nanobanana_get_task or batch status checks with nanobanana_get_tasks_batch . Choose among supported models :...

Современный редактор с ИИ полезен ровно настолько, насколько он опирается на проверяемые данные. При работе с меняющимися библиотеками, облачными SDK, релизами фреймворков и редкими сбоями одной памяти модели недостаточно: сведения быстро устаревают, а уверенный ответ может оказаться неверным. Практичный способ сократить этот разрыв — подключить поиск как инструмент Model Context Protocol (MCP) и дать агенту в VS Code возможность запрашивать свежие источники в ходе задачи. Ниже — инженерный сценарий на основе документации Ace Data Cloud: установка расширения, хранение ключа в защищённом хранилище VS Code, проверка вызова, а также отдельные HTTP-примеры для диагностики интеграции. Подход ориентирован на разработчиков, работающих с несколькими моделями и желающих отделить поиск фактов от генерации кода. Что меняет MCP в редакторе MCP описывает единый способ, которым клиент с ИИ обнаруживает и вызывает внешние инструменты. В данном случае поисковый инструмент возвращает результаты ве...

When an AI coding assistant lives outside your editor, every useful change can turn into a copy-paste loop: ask in a terminal, inspect files in the IDE, apply diffs manually, then repeat. The Claude Code JetBrains plugin closes that gap by letting you run claude from the same project context while keeping JetBrains-native features such as diffs, selected code, open tabs, and diagnostics in the workflow. What you can do With the JetBrains integration configured, you can use Claude Code from IDEs such as IntelliJ IDEA, PyCharm, WebStorm, GoLand, PhpStorm, and Android Studio. The workflow is especially useful when you want an agentic coding session that can reason about the same files you are editing, then show code changes in the IDE instead of forcing you to reconstruct patches by hand. The integration supports several practical behaviors: Diff view: code changes are displayed in the IDE’s Diff viewer. Context selection: selected code and the current tab can be shared wit...

Image editing APIs are easy to demo, but harder to put into a production workflow: you need to keep the source structure stable, pass references cleanly, choose an output size intentionally, and avoid blocking your application while a render is running. What you can do The OpenAI Images Edits API on Ace Data Cloud exposes image editing through POST /openai/images/edits . The documented interface supports GPT Image models such as gpt-image-1 and gpt-image-2 , plus the nano-banana family through the same editing endpoint. For this guide, we will focus on gpt-image-2 , because the documentation describes it as stronger for structure preservation, text retention, direct URL input, base64 input, and high-resolution redrawing. In practical terms, that makes it useful for builder tasks like: turning an existing infographic into a dark-mode version while keeping its layout intact; replacing the style or environment of a product image while preserving key object placement; combining m...

When you wire image generation into a product, the challenge is not just producing one image. It is designing a workflow that handles prompt-only generation, reference-image editing, traceable results, and asynchronous completion without splitting your backend into unrelated code paths. What you can do The Nano Banana Images API exposes a single image endpoint for two practical workflows: text-to-image generation and image editing. The documented base URL is https://api.acedata.cloud , and the endpoint is POST /nano-banana/images . You choose the workflow with the action field. action: generate creates images from a text prompt . action: edit edits or combines existing images using image_urls and a prompt . count requests 1 to 4 images and defaults to 1. callback_url lets your service receive a POST JSON callback when work completes. How it works Requests are JSON. The required fields for generation are action and prompt . Editing also needs image_urls , an array with at l...

If your product needs spoken output, the hard part is rarely the first audio file; it is choosing the right request shape, handling long text safely, and keeping the integration simple enough to maintain. What you can do The Fish TTS endpoint on Ace Data Cloud gives you a direct HTTP interface for turning text into audio. The documented endpoint is POST https://api.acedata.cloud/fish/tts . It accepts a JSON body, authenticates with a platform token, and returns an audio_url for synchronous requests. The useful thing for builders is that the request body keeps the same field naming as the upstream Fish Audio TTS API, with one Ace Data Cloud extension: callback_url for asynchronous completion callbacks. That makes it practical to start small with a single curl request and later add production behavior for longer text. Generate mp3 , wav , or pcm output. Use a cloned voice via reference_id , or provide inline references . Control delivery details such as sample_rate ...