Razi Media Tools

Re-encode a single raster image to webp, jpeg, png or avif, optionally resizing it and/or converting it to grayscale. HEIC/HEIF input is converted to JPEG first, and SVG input is rasterised at 300 DPI, fitted inside 800x800 unless width or height is given. Lossy for webp, jpeg and avif at any quality below 1.0. Raster images only: a PDF or a video is rejected, and neither can be re-encoded anywhere on this server. Output shape depends on size: an input under 5MB is processed in-app and the encoded image bytes are returned, while anything larger is sent to razi.pro's worker and the reply is JSON { url, size, metadata } pointing at a hosted copy instead of bytes. Paid compute; 30 calls per hour per IP. There is no upload channel over MCP: pass `fileUrl`, a URL in razi.pro's own storage; third-party URLs are rejected. Obtain one by uploading the image over the REST API first (POST /api/v1/tools/execute with the file attached).

Render text or a URL as a QR code image. Returns JSON { dataUrl, text, size } where dataUrl is a base64 PNG data URI embedded in the response — not a hosted link, so nothing is stored and the image cannot be fetched later. Runs locally and costs nothing. Writing only — it cannot read or decode an existing QR code. A long payload makes a denser, less scannable code, so shorten the address by other means before encoding it if you can.

Generate a new image from a text description with a diffusion model. Returns a single PNG; over MCP it arrives inline when under 1MB and otherwise as a stored URL that stays retrievable for about 24 hours. This invents an image from scratch — it cannot edit, upscale or restyle a picture you already have. Use compress_image to re-encode or resize an existing file. Requires a signed-in razi.pro account; an anonymous call is rejected with 401. Paid compute, 20 images per hour per account, and generation can take tens of seconds. Providers are tried in turn (Fireworks FLUX.1-schnell, Hugging Face FLUX.1-schnell, SDXL, Cloudflare SDXL, Replicate), so the model that actually ran varies with availability and there is no seed or size control. No two calls give identical output, and the image is not automatically hosted anywhere permanent.

Cut one storyboard, collage or grid image into its separate panels and return them as a ZIP, one file per panel in reading order. Over MCP the ZIP is not inlined: it comes back as a stored URL that stays retrievable for about 24 hours. Two modes. Give both rows and cols for an exact equal division, which is free of model cost and predictable. Omit them and a vision model locates the panels, excluding borders, gaps and captions — better on uneven layouts, but it is a paid inference whose panel count and crops can vary between runs, and it fails with 400 if it finds nothing. Panels are cropped, never resized; a lossy re-encode at quality 90 is applied for jpeg and webp. This divides one image into several — it does not shrink a file (use compress_image), and it cannot take a PDF apart. Paid compute; 20 calls per hour per IP. There is no upload channel over MCP: pass `fileUrl`, a URL in razi.pro's own storage; third-party URLs are rejected. Obtain one by uploading the image over the REST API first (POST /api/v1/tools/execute with the file attached).