The design workspace
your agents can use.
Most design tools are built for hands and eyes. Clearly is built so an AI agent can generate editable art, see a shared canvas, and act on it — the same generate-see-act loop a designer runs, exposed as tools and billed to one plan.
Your agent hand-rolls editable paths like these — it can post-process, diff, or hand them to a human.
What is a design tool for AI agents?
It is a design workspace an agent operates directly — not a human app with an API bolted on. In Clearly, an AI agent can generate editable vector or raster art over MCP or the CLI, perceive a live canvas (nodes, selection, even the Skia-drawn chrome), and drive it — place, restyle, export — then hand the same editable file to a person to finish. Agent work and human work draw the same metered plan.
A designer's loop, given to an agent
A human designer makes a mark, looks at the result, and adjusts. Clearly gives an agent all three verbs — not just the first one an image API stops at.
Generate
Make editable vector & raster art from a prompt — headless, no browser.
clearly_canvas_act over MCP — hand-rolled SVG + paths onto a real canvas. Or one beehaven CLI call.
Perceive
See the canvas — nodes, selection, viewport, even the Skia-drawn chrome.
canvas-perceive returns a structured CompositionRoom (or a live PNG).
Drive
Act on the canvas — place, paste, restyle, export — like a hand on the mouse.
canvas-invoke dispatches registered editor actions to a live tab.
Perceive + drive are what make Clearly a workspace for agents, not just a generator. The agent isn’t blind to the document it’s editing.
An image API returns a picture. This runs the design loop.
The gap between a generation endpoint and a workspace an agent can actually operate.
| Feature | Clearly (agent-native) | Generic image API | Human-only design tool |
|---|---|---|---|
| Generate art from a prompt | ✓ | ✓ | — |
| Output stays editable (vectors) | ✓ | — | ✓ |
| Agent can see the canvas | ✓ | — | — |
| Agent can act on the canvas | ✓ | — | — |
| Human can refine the same file | ✓ | — | ✓ |
| One metered plan for agents + people | ✓ | — | — |
Connect however your agent already runs
The same generation + canvas engine behind the Clearly studio, reachable four ways. Pick the one that fits your stack — nothing to deploy.
From one icon to a standing asset pipeline
Anywhere an agent needs to make or edit a picture instead of describing one.
Consistent design systems
Pin one style across a fleet of calls so 200 generated icons all match — editable SVG that drops into your component library.
Build-time asset pipelines
An agent reads a manifest in CI and emits the missing illustrations, OG images, and spot icons — no designer in the critical path.
On-brand at scale
Ground every agent in Company Brain so a thousand marketplace thumbnails or product badges come out in your palette and voice.
Agent drafts, human finishes
The agent generates onto a canvas via a compositionId; a teammate drags nodes and recolors paths. The un-copyable round trip.
Bots that return real art
A Slack, Discord, or support bot that answers with an actual sticker or diagram — generated on the fly, posted back as a URL.
Creative coding agents
Give a coding agent a drawing primitive: it reasons about a layout, calls the tool, inspects the returned paths, and iterates — a real loop, not prompt roulette.
Token, point, call
Sign in
OAuth in the browser the first time your client connects — nothing to copy or rotate. Headless job that can’t open a browser? Mint an agent-bound token in the Agents modal.
Point your client
Add the hosted MCP endpoint or install the beehaven CLI — nothing to deploy. Claude Code and Cursor are one line each.
Generate, perceive, drive
Your agent now has design tools in its loop — make art, read a canvas, act on it — all billed to your AI pool.
Software for agents, answered
01What is a design tool for AI agents?+
02What is an MCP design server?+
03Which agents and clients does it work with?+
04How is this different from an image-generation API?+
05How is agent usage billed?+
06Do the results stay editable for a human to finish?+
07Why build software for agents at all?+
Go deeper on each surface
MCP server
Generate editable SVG & raster from Claude, Cursor, or any MCP client — headless, per-call cost.
Clearly MCP
Your workspace behind one endpoint — context search, decisions, skills, and the canvas, for any MCP client.
A canvas agents can see
canvas-perceive + canvas-invoke — the read/write pair that lets an agent operate a live canvas.
Beehaven CLI
Drive generations and your whole agent cloud from the terminal or a CI job.
Company Brain
Ground agents in your brand DNA + org knowledge so output is on-brand by default.
For your team, too
The same canvas where people collaborate in real time — agents are just more participants.
The same agent, pointed at a storefront
Shopify AI agent
The commerce build of the agent stack — it reads your catalogue, answers in your voice, and acts on the store rather than just chatting about it.
Shopify AI chatbot
Answer product questions on the storefront around the clock, grounded in real inventory instead of a canned FAQ.
Shopify over MCP
Point Claude or Cursor at a live store — the same endpoint the design tools use, scoped to commerce actions.
Product descriptions
Generate listing copy from the product data you already have, in the voice the rest of the store is written in.
Order tracking
Hand off “where is my order” to an agent that can actually look it up, which is most of a support queue.
Give your agents a design tool
Mint a token, point your client at the hosted server, and let your agents generate, perceive, and drive — metered against one AI pool for your whole team.