A self-updating MCP system that analyzes design and code inputs with an LLM, refines them through conversation, and crystallizes approved patterns into a local skill library for MCP agents.
MCP-first UI/UX review layer for AI-generated frontends. Enables reviewing web pages via URL, capturing screenshots, extracting layout metrics, and generating structured repair plans for agents.
An MCP server for in-loop design review of web previews. It enables agents to submit a preview URL, receive structured findings with suggested fixes, and recheck after applying changes, while never editing code itself.
An MCP server implementing a 7-stage agentic frontend workflow—from design audit to PR review—including AI-driven component generation, browser validation, E2E testing, and CI self-healing.