image-processing

Image processing for AI agents: resize, convert, compress, crop, and web-ready AI-generated images.

От сообществаРаботаетБез входаГлобальныйБесплатноТолько чтение

Что умеет

    Какие данные видит

    Нужен ли аккаунт

    Не нужен: сервер работает без входа

    Image processing for AI agents: resize, convert, compress, crop, and web-ready AI-generated images.

    Как подключить

    Как подключить image-processing к Claude

    Адрес сервера, который нужно вставить в настройках Claude:

    https://api.pictomancer.ai/mcp

    1. Откройте Claude (сайт claude.ai или приложение для компьютера).
    2. Перейдите в Настройки → Коннекторы (в английском интерфейсе: Settings → Connectors).
    3. Нажмите Добавить пользовательский коннектор (Add custom connector).
    4. Вставьте адрес сервера, скопированный ниже, в поле URL удалённого MCP-сервера и нажмите Добавить.
    5. В чате нажмите + → Коннекторы и включите новый коннектор.

    Пользовательские коннекторы доступны на тарифах Free, Pro, Max, Team и Enterprise. На Free можно добавить только один. В Team и Enterprise коннектор сначала добавляет владелец организации в Настройки организации → Коннекторы.

    Авторизация

    После нажатия Добавить откроется окно входа в сервис. Войдите под своим аккаунтом и подтвердите доступ. Пароль Claude не видит.

    Как подключить image-processing к ChatGPT

    Адрес сервера, который нужно вставить в настройках ChatGPT:

    https://api.pictomancer.ai/mcp

    1. Откройте ChatGPT в браузере (chatgpt.com). Нужен тариф Plus, Pro, Business, Enterprise или Edu.
    2. Один раз включите режим разработчика: Настройки → Приложения → Дополнительные настройки → Режим разработчика (Settings → Apps → Advanced settings → Developer mode).
    3. Откройте Настройки → Коннекторы и нажмите Создать (Create).
    4. Заполните форму: Название (любое), Описание (одна фраза, что делает сервис), URL MCP-сервера (скопируйте ниже).
    5. В поле Аутентификация выберите OAuth, если сервис требует вход, иначе Нет. Нажмите Создать.
    6. В новом чате откройте + → Приложения/Коннекторы и включите коннектор.

    Название раздела у OpenAI менялось (Connectors → Apps/Plugins). Если пункт называется иначе, ищите «режим разработчика» в настройках. В рабочих пространствах Business/Enterprise администратор должен разрешить пользовательские коннекторы.

    Авторизация

    При первом использовании ChatGPT откроет окно входа в сервис. Войдите и подтвердите доступ.

    Как подключить image-processing к Cursor

    Адрес сервера, который нужно вставить в настройках Cursor:

    https://api.pictomancer.ai/mcp

    Быстрый способ: нажмите кнопку Открыть в Cursor ниже, Cursor сам предложит добавить сервер.

    Вручную:

    1. В Cursor откройте Settings → Cursor Settings → MCP и нажмите Add new global MCP server.
    2. Вставьте JSON, скопированный ниже, в открывшийся файл ~/.cursor/mcp.json (для одного проекта: .cursor/mcp.json в корне проекта).
    3. Сохраните файл. Сервер появится в списке MCP; при необходимости пройдите авторизацию по кнопке рядом с ним.

    Авторизация

    Если сервис требует вход, рядом с сервером в списке MCP появится кнопка авторизации.

    Список инструментов сервера (10)

    Технические названия из tools/list. Нужны только разработчикам.

    get_format_infoGet supported formats and options Returns supported output formats and their configurable options. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json
    estimate_costEstimate the price of an operation Returns the exact USD price this API would charge for an operation on an input of the given size, without fetching or processing anything. Free. Use it before paying: send X-Max-Cost-USD on the real request to have the API refuse (412) instead of charging more than you allowed. The list price is returned even when the request could end up free (free tier, or a compress that does not shrink the file). ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **Example Response:** ```json { "operation": "Operation", "price_usd": 1.0, "base_usd": 1.0, "surcharges_usd": {}, "size_multiplier": 1.0, "within_free_tier": true, "free_tier_remaining": 1, "currency": "Currency", "network": "Network" } ```
    analyze_imageAnalyze an image Fetch an image from a URL or base64 and return its metadata: size in bytes, pixel dimensions, source format, and what it costs every supported vision model in tokens. Always free. Dimensions are omitted if the image header cannot be read. Also reports whether the input carries a C2PA (Content Credentials) manifest and in which container; the manifest is not validated. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **Example Response:** ```json { "size_bytes": 1, "c2pa_manifest": true } ```
    resize_imageResize an image Scale an image by a factor, or fill an exact box. Use 'scale' for uniform scaling, or 'scale_x'/'scale_y' for independent axes (float factors, e.g. 0.5 = half size). Alternatively set 'width'+'height' for fill mode: resize and smart-crop to those exact dimensions in one call (optional 'gravity', default attention). The two modes are mutually exclusive. Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```
    compress_imageCompress an image Re-encode an image with quality/format options to reduce file size. Supports jpeg, png, webp, tiff, gif. Instead of a q number you can set quality_target (0-1]: the smallest file with SSIM at or above the target, searched on the worker (jpeg, webp, avif; flat surcharge; outcome reported in X-Pictomancer-Quality-* headers). If the output is not smaller than the input, the request is free (X-Pig-Billed: 0) and does not consume free-tier quota. Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```
    convert_imageConvert image format Convert an image to a different format (jpeg, png, webp, tiff, gif, avif). Optionally set quality, strip metadata, enable lossless mode (webp, avif), or tune encoder effort (avif). Instead of a q number you can set quality_target (0-1]: the smallest file with SSIM at or above the target, searched on the worker (jpeg, webp, avif; flat surcharge; outcome reported in X-Pictomancer-Quality-* headers). Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```
    crop_imageCrop an image Extract a rectangular region from an image, in one of three mutually exclusive modes. Manual: give the top-left corner (x, y) and dimensions (width, height) in pixels. Smart crop: give 'gravity' (attention, entropy, centre) plus width and height; the window is picked automatically, clamped to the source if the target is larger. Trim: set 'trim: true' (optional 'threshold') to remove a uniform background border via content detection; the applied rect is reported in X-Pictomancer-Trim-* headers. Optional enhancement modifiers: denoise (1-3), equalize, sharpen (applied denoise -> equalize -> op -> sharpen). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```
    optimize_for_visionResize an image for a vision model Resize an image to the largest size a given vision model still benefits from, and report what it costs that model in tokens before and after. Every provider downscales oversized input before counting tokens, so this alone saves bytes and upload latency rather than tokens. Pass max_tokens to trade resolution for tokens: that lever is continuous on Claude, unavailable on OpenAI (cost follows the aspect ratio alone), and on Gemini reaches only a flat 258. An image already within budget is returned untouched and free (X-Pig-Billed: 0). ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```
    optimize_generated_imageOptimize an AI-generated image for the web The step after image generation. gpt-image, DALL-E, Flux, Midjourney and Stable Diffusion hand back 2-8 MB PNGs; this returns the same picture as a web-ready webp (default), avif, jpeg or png, metadata stripped, transparency kept on webp/avif/png. Optional max_dimension caps the longest side (never upscales); optional q or quality_target (smallest file with SSIM >= target, flat surcharge) control quality. Same price as convert. If the result is not smaller than the input it is still returned but free (X-Pig-Billed: 0). X-Pictomancer-Bytes-Before/-After/-Saved-Percent report the saving. The input's C2PA manifest, if any, is reported in X-Pictomancer-C2PA-Input but is not carried over: re-encoding invalidates it. ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```
    image_pipelineRun a multi-step image pipeline Chain multiple operations (resize, compress, convert, crop) in sequence. The image is fetched once, then each operation is applied to the output of the previous one. Max 10 operations per pipeline. ### Responses: **200**: Processed image binary (Success Response) Content-Type: application/json Content-Type: image/jpeg **Example Response:** ```json "string" ``` Content-Type: image/png **Example Response:** ```json "string" ``` Content-Type: image/webp **Example Response:** ```json "string" ```