Fudge: web-design reference database for AI agents
Fudge is a web-design reference database that lets AI agents search over 1,600+ websites for design inspiration instead of generating generic interfaces from scratch. It solves the problem of AI producing bland, template-like designs by providing real-world references.
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Searchable registry of 10k+ shadcn UI blocks for AI agents
A searchable directory that indexes over 10,000 shadcn UI blocks from dozens of community registries. It solves the problem of developers wasting time digging through scattered registries or burning tokens to generate UI components from scratch. The platform likely uses LLMs to power search or agent integration, enabling AI agents to fetch UI blocks on demand.
MCP server feeding live design tokens from real products to LLM agents
An MCP server that provides structured design tokens (colors, typography, spacing, etc.) extracted from live DOM of real products like Linear and Supabase. LLM code agents use these tokens via MCP to generate UI that matches a specific product's design system, avoiding generic outputs. Solves the problem of agents producing bland, average UI by giving them concrete design references.
UI/UX audit tool that generates an AUDIT.md file for AI
A tool that audits the UI/UX of a website and produces an AUDIT.md file, designed to help developers and designers get actionable feedback in a format that AI tools can process. It solves the problem of manual UI/UX review by automating the audit and outputting structured markdown.
AI portfolio builder that creates project-focused portfolios from descriptions
Denetor is an AI tool that generates professional portfolios focused on projects, not personal websites. Users describe their work and the AI structures it to highlight what was built, why it matters, problems solved, and impact created. It solves the problem of time-consuming portfolio curation for professionals.
Narada: a browser built for AI agents, under user control
Narada is a browser designed specifically for AI agents to interact with web content programmatically, while keeping the user in control. It uses LLMs to enable agents to browse, extract, and act on web pages, solving the problem of giving agents a safe, controllable web interface.