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Create, lay out, render, and lint wireframes through an MCP server.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "wiri" yet — see the docs or source repo.
Create a wireframe for an e-commerce product detail page with a top nav, product image area, price and buy button, and review list, using a semantic structure for each section.
A page wireframe represented as a semantic scene graph with a basic layout.
Move the primary button below the form on the login page, add a 'Forgot password' link, and keep the overall layout consistent without using absolute coordinates.
An updated wireframe structure and re-laid-out result showing the structural edits.
Render this dashboard wireframe and check for layout or structural lint issues, then list the findings.
A deterministic render plus a list of lint findings for the wireframe.
Designers or product managers can have an LLM produce page wireframes instead of only static descriptions. The tool stores each screen as a semantic scene graph, making further edits easier.
When UI elements need frequent additions or removals, layouts can be adjusted structurally without relying on absolute coordinates. This is useful for iterative model-driven interface editing.
Developers or design teams can review deterministic render outputs after edits and use lint findings to inspect issues. This helps verify whether wireframe changes match expectations.
Wiri is a headless wireframing MCP server designed for LLM operation. It stores interfaces as semantic scene graphs and provides layout, rendering, and linting capabilities.
It stores each screen as a small semantic scene graph and lays out elements without absolute coordinates. This makes it better suited for structured editing and iterative changes.
The provided material does not include installation steps, runtime requirements, or key details. See the source repository for specifics.
Helps developers find and generate WireUI v2 component and icon usage.
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Access remote MCP tools with GitHub OAuth, utility actions, and image generation.
Collect interactive user feedback before AI takes actions in development workflows.
Assist with visible web forms and require approval before any filling actions.