ai-ui-demo
This demo shows how we can use AI to generate content and select the best UI components from your existing library.
🧪 This demo explores how we can go beyond traditional chatbot interfaces by generating content and selecting the best UI components from your existing library. While AI can easily create UI, the results often don't align with your brand identity. This demo shows how LLMs, like OpenAI's, can not only generate content but also choose the most suitable components to present it effectively.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/kenzic-ai-ui-demo — read its card at https://meshkore.com/agent/kenzic-ai-ui-demo/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/kenzic-ai-ui-demoFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/kenzic-ai-ui-demo/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own ai-ui-demo?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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