Give your agent eyes, and an eraser
Your AI agent writes code, searches the web, and manages files. Give it image editing too. Peelaway's API is built for autonomous workflows: discoverable, predictable, and simple enough for any agent to orchestrate.
Drop your image here
or click to browse. PNG, JPG up to 20MB
Built for autonomous workflows
Three layers of agent discoverability, plus an API simple enough that any agent can use it without human guidance.
SKILL.md: agent skill definition
A structured skill file that tells coding agents exactly how to use Peelaway: when to invoke it, the 3-step workflow, request/response formats, and error handling. Drop it into Claude Code, Cline, or any agent that supports skill files.
llms.txt: LLM-readable service description
A plain-text service overview optimized for LLM consumption. Describes what Peelaway does, lists all endpoints, and links to the OpenAPI spec. Discoverable at /llms.txt.
OpenAPI spec: machine-readable API contract
Full OpenAPI 3.0 schema at /openapi.json. Any agent framework with HTTP tool support can auto-generate client code or use it for function calling.
Three-endpoint async API
Submit (POST /process), poll (GET /status), download (GET /result). Simple enough for any agent to orchestrate without complex state management.
Base64 in, base64 out
Images are sent and received as base64-encoded strings in JSON. No multipart uploads, no file handling, just JSON payloads that agents handle natively.
Pay only for what you run
No idle cost and no infrastructure to manage. Agents call Peelaway on demand and pay only for the images they process, a fraction of manual editing costs.
APIs that agents actually understand
Most image editing APIs are designed for human developers reading documentation pages. They have complex auth flows, multipart uploads, webhook callbacks, and SDK-specific patterns that agents struggle with.
Peelaway is agent-first. Base64 JSON in, base64 JSON out. Three endpoints, deterministic status codes. Plus /SKILL.md and /llms.txt that tell agents exactly what the service does and how to use it, before they make a single API call.
Authenticate with a single pk_ bearer key in the Authorization header. No OAuth handshake, no per-call signing.
Submit → poll → download. Processing takes 30s to 2min. Agents can do other work while waiting, or poll in a loop.
JSON responses with consistent schemas. Status is always pending, processing, done, or error. No ambiguous outputs for agents to parse.
400 for bad input, 404 for unknown job, 202 for not-ready-yet. Agents can branch on status codes without parsing error messages.
Frequently asked questions
Peelaway for other industries
Works with every agent ecosystem
Any AI tool that can make HTTP requests can use Peelaway. Here's what's already compatible.
Coding Agents & AI IDEs
Agent Frameworks
MCP-Compatible Clients
LLM Providers & Platforms
Automation & Workflow
Agent integration in 30 seconds
Discover, submit, poll, download. That's the whole workflow.
# LLM-readable overview
curl https://api.peelaway.io/llms.txt
# Structured skill definition
curl https://api.peelaway.io/SKILL.md
# Machine-readable spec
curl https://api.peelaway.io/openapi.json# Submit
POST /process
{"image": "<base64>"}
# → {"job_id": "abc123"}
# Poll
GET /status?job_id=abc123
# → {"status": "done"}
# Download
GET /result?job_id=abc123
# → {"image": "<base64>"}