rendry

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rendry.io에서 보기이 MCP 사용해 보기스폰서

문서

Rendry documentation

REST API and MCP server for rendering images and PDF documents from templates. External AI clients can supply layouts and copy through MCP; the rendering pipeline does not run a generative image model. Separate ML tools process existing images: rembg/U2Net removes backgrounds, and optional SAM3 through fal.ai segments objects. This page summarizes the interactive documentation.

Getting started

Create an account, design a template in the visual editor (or clone one of 51 gallery templates), generate an API key in Settings → API Keys, and render:

curl -X POST https://rendry.io/api/v1/render/sync \
  -H "Authorization: Bearer sk_live_..." \
  -H "Content-Type: application/json" \
  -d '{"preset_id": "your-template", "dynamic_data": {"title": "Hello"}}'

The response contains result_url of the finished PNG. Typical render: ~1-3 s.

What the docs cover

  • Authentication; API keys (Bearer sk_live_...) and OAuth 2.1 for MCP clients
  • Templates and presets; JSON DSL, layers (text, image, shape, QR, barcode, group), {variables} and dynamic_data
  • Rendering; sync (up to 25 s), async with webhooks, batches up to 10 images per call
  • Connecting AI agents; remote MCP endpoint https://rendry.io/api/v1/mcp, 33 tools, drafts at 0.1 of a credit
  • Assets; uploading images and custom fonts, background removal, stock photo search
  • Limits; canvas up to 6144×6144 px, 40 layers, plans and quotas

Machine-readable: llms.txt, llms-full.txt, OpenAPI, MCP manifest.