Add UI Knowledge & Usage Pattern Support for AI (Similar to gluestack-ui MCP)

I would like to propose adding built-in support for UI knowledge and usage patterns in Ignite, similar to the concept of MCP (Model Context Protocol) used by gluestack-ui.

The goal is to make Ignite more AI-friendly by providing structured, machine-readable context about UI components, design patterns, and best practices. This would enable tools like Copilot or Cursor to better understand how to generate, compose, and reuse UI within an Ignite-based project.

Specifically, this could include:

A standardized way to define UI components and their usage patterns
Documentation or metadata that describes component props, variants, and composition rules
Clear conventions for layout structures (e.g., screens, containers, shared UI)
Integration or compatibility with AI tooling for improved code generation and consistency

This enhancement would significantly improve developer experience, especially for teams leveraging AI-assisted development, by reducing ambiguity and enforcing consistent UI patterns across the codebase

The issue names no files, tests, or entry points. Begin by reviewing Ignite's existing UI component and layout conventions, then compare them with the gluestack-ui MCP approach and the stated Copilot or Cursor use cases. Done would require an agreed scope for component metadata, usage patterns, layout conventions, and AI-tool integration.

Written by the indexing model from the issue text.