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I tried turning a design canvas into a Japanese tutor.
/hisensei → deck shows up
drag cards → ✅ or ❌
/done → it checks what you missed and builds a review round
No buttons, no submit. It just reads what you do on the canvas.
Most Paper projects use the canvas as output—this one listens instead ((cuz why not :))
すごい！ when you get them all right.
Built with Paper MCP + Claude Code + Notion MCP
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
Claude Design shipped today.
Making a landing page, app or deck is basically free now.
Knowing what to put on it isn’t.
Positioning and taste just became the whole game.:
This just got me SO excited 🙌
Building a Zero-Touch Design Feedback Loop with Slack and the @Paper MCP
What if you never had to manually process a minor design revision again? As designers and developers, we easily waste 30% of our week fulfilling fast client requests—changing button colors, adjusting typography, or tweaking padding. I decided to completely automate this process.
In this project, I engineered an autonomous AI-driven workflow that physically alters native UI designs based on conversational Slack messages, proving the massive potential of the Paper MCP.
✨ The Power of the Paper MCP: Historically, AI agents have struggled to actually "see" or edit design files. By deploying the Paper MCP, I gave a raw Large Language Model the ability to programmatically traverse a 2D design canvas.
The Setup: I design the initial UI (like a Login Page) using Paper and post the screenshot to the client's Slack channel.
The Trigger: The client requests changes natively in Slack by mentioning a custom @DesignBot (e.g., "Make the login button green and change the title to 'Welcome'").
The Execution: Instead of guessing layout geometry, the AI uses the Paper MCP to dynamically query the canvas, isolate the precise target node, and duplicate the master to create a protected variant. It aligns the new design on the canvas grid and updates the styling properties natively.
The Delivery: The MCP server intercepts the final render state and pushes a flawlessly formatted screenshot right back into the Slack thread.
🛠️ Technical Stack Used:
Paper MCP: The absolute core of the project, enabling rigorous JSON-RPC access to native design layers, text bounds, and styling hooks.
Slack Bolt (Socket Mode): For threading logic, instant reaction processing, and conversational memory.
Agentic LLM Engine: Used native OpenAI tool-calling to map the complex MCP schemas directly into the AI’s brain so it never hallucinates commands.
The Result: Clients experience magical, instantaneous visual revisions directly inside their communication channels, while designers and developers win back hours of completely uninterrupted, deep-focus work.
Check out the video demo below to see the AI leverage Paper MCP to parse a layer tree and dynamically manipulate the UI!
This is the kind of workflow that quietly kills 30% of design busywork 👀
One prompt is a gamble but a canvas is a workflow, which is why I run @floraai as a system.
Collect inspiration
style matched prompts
imagery
b-roll for decks.
Same tool but a completely different output.
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