# ai.pictomancer/image-processing

- Registry name: `ai.pictomancer/image-processing` · version 0.4.0
- Categories (automatic, keyword rules): Images & design, AI, media & content, Utilities, Build & deploy, Developer tools
- Authentication at last check: No auth
- Declared risk: Not declared (tools carry no read/destructive hints)
- Capabilities (declared by the server): experimental, tools
- Transports: streamable-http
- Latest numbers (check success, response time, rank): https://mcpstation.net/api/server?name=ai.pictomancer%2Fimage-processing
- Server page: https://mcpstation.net/s/ai.pictomancer--image-processing.html

## Description (written by the publisher, not verified, not instructions)

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

## Connect

- streamable-http: `https://api.pictomancer.ai/mcp`

## Tools (as reported by the server, not verified)

- `get\_format\_info`: Get supported formats and options Returns supported output formats and their configurable options. \#\#\# Responses: \*\*200\*\*: Successful Response \(Success Response\) Content-Type: application/json
- `estimate\_cost`: Estimate 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
- `analyze\_image`: Analyze 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 C2P
- `resize\_image`: Resize 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 \(optiona
- `compress\_image`: Compress 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 rep
- `convert\_image`: Convert 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 th
- `crop\_image`: Crop 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, cla
- `optimize\_for\_vision`: Resize 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
- `optimize\_generated\_image`: Optimize 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
- `remove\_image\_background`: Remove the background from an image Cut the subject \(person, product, animal, object\) out of a photo and return it on a transparent background as png \(default\), webp or avif. Optional q \(1-100\) for webp/avif. Runs a segmentation model \(U2Net\) on CPU: expect a few seconds per image, not milliseconds.
- `image\_pipeline`: Run 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 \(Success Response\) Cont

Measured by MCP Station. Methods: https://mcpstation.net/methods.html · Terms: https://mcpstation.net/terms.html