AI tool comparison
Nicelydone MCP vs trellis-mac
Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.
Design
Nicelydone MCP
140k real product screens as design context for AI agents building UIs
75%
Panel ship
—
Community
Free
Entry
Nicelydone MCP is a Model Context Protocol server that gives AI coding agents access to over 140,000 real screens, user flows, and UI components from shipped consumer and B2B products. When an agent is building an interface, it can pull authentic reference designs matching the target use case instead of generating generic layouts from training data alone. The server integrates with Claude, Cursor, VS Code, and any MCP-compatible client. Designers and developers can query the library by UI pattern type (empty states, onboarding flows, settings pages, etc.) and the agent incorporates those real-world examples as visual context. The core insight is that AI models trained on internet data produce 'average' interfaces — they know what UI elements exist but not which combinations are actually good. Nicelydone injects a curated signal of real quality product design into the generation process, addressing one of the most consistent weaknesses in AI-generated frontends.
Creative Tools
trellis-mac
Run Microsoft's image-to-3D model natively on Apple Silicon — no NVIDIA needed
75%
Panel ship
—
Community
Free
Entry
trellis-mac is a community port of Microsoft's TRELLIS.2 image-to-3D model that runs entirely on Apple Silicon via PyTorch MPS — no NVIDIA GPU required. A single photo goes in, a 400,000-vertex mesh comes out in roughly 3.5 minutes on an M4 Pro, with no cloud dependencies. TRELLIS.2 is one of the strongest open-weights models for single-image 3D reconstruction, producing mesh quality that previously required either expensive NVIDIA hardware or cloud API calls. This port handles the MPS-specific tensor quirks and memory management that make running the model locally on Apple hardware nontrivial. The HN Show HN thread hit 84 points and generated active testing discussion, with multiple users confirming it runs as advertised on M1 Max and M2 Ultra hardware. For 3D artists, indie game developers, and VR/AR creators, the ability to generate production-quality meshes from reference photos on a MacBook is a meaningful workflow unlock. The bottleneck shifts from hardware access to the quality of your reference photography.
Reviewer scorecard
“Anyone who's tried to get Claude or GPT to generate a non-hideous onboarding flow knows the pain. Plugging in 140k real UI patterns as context is the right fix — you're giving the model a design vocabulary instead of hoping it learned one. Shipped three features this week with notably better first-pass UI quality.”
“Solid port work — handling MPS tensor compatibility for a model this complex isn't trivial. The 3.5-minute generation time on M4 Pro is competitive and the 400K vertex output is actually usable for game assets without heavy retopology.”
“Reference design libraries are only as good as their licensing. It's unclear whether Nicelydone has rights to use all 140k screens commercially, and using an MCP server built on potentially scraped UI assets could expose teams to legal risk. Verify the terms before integrating into client work.”
“The original TRELLIS.2 still runs faster and with higher fidelity on a dedicated NVIDIA GPU. 3.5 minutes is fine for experimentation but too slow for iterative production workflows. Also, single-image 3D reconstruction still has consistency issues with complex objects.”
“This is a preview of how design systems will work in an agent-first world — not static Figma files but queryable knowledge bases that agents can pull from at generation time. Nicelydone's approach could evolve into industry-standard design context infrastructure, the way npm became infrastructure for code.”
“This is Apple Silicon democratization in action. The fact that state-of-the-art 3D generation now runs on laptop hardware means 3D assets will be generated ad-hoc at every creative workflow stage within two years.”
“As a designer this is genuinely exciting. I can now describe a pattern ('progressive disclosure pricing table with annual toggle') and the agent pulls a real example from a product people actually use, then implements from that reference. It's like giving the AI a proper inspiration board before it starts designing.”
“As a 3D artist, being able to photo-scan real objects on my Mac without a render farm or API is a genuine workflow breakthrough. The mesh quality from TRELLIS.2 is good enough to use as a base for sculpting and texturing.”
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