AI tool comparison
Nicelydone MCP vs TRELLIS.2 for 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
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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.2 for Mac
Microsoft's image-to-3D model finally runs on your M-chip Mac
75%
Panel ship
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Community
Paid
Entry
TRELLIS.2 for Mac is a community port that brings Microsoft's powerful image-to-3D generation model to Apple Silicon, replacing every CUDA dependency with Metal-accelerated alternatives. Feed it a single photograph and it outputs a 400K+ vertex mesh with baked PBR (physically-based rendering) textures for metallic, roughness, and base-color properties — as a GLB file ready for Blender, game engines, or AR apps. On an M4 Pro with 24GB RAM, the process takes about 5 minutes. The port is technically substantial: sparse 3D convolution uses Metal acceleration (with PyTorch fallback), mesh extraction is reimplemented in Python, attention uses PyTorch's SDPA, and texture baking leverages Metal rasterization. Every hardcoded CUDA call throughout the original codebase was patched to use the active device dynamically. The result is a model that was previously Mac-inaccessible now running natively without any cloud dependency. For 3D artists, game developers, and AR/VR creators on Apple Silicon — which is most of them these days — this removes a significant barrier. The upstream TRELLIS.2 model is MIT licensed; RMBG-2.0 background removal requires a BRIA commercial license for business use. With 202 HN points, this hit a nerve with creators frustrated that Mac hardware keeps getting excluded from serious ML workflows.
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.”
“This is the kind of community port that changes workflows. TRELLIS.2 was genuinely out of reach for Mac users; this brings it home. 5 minutes per mesh on an M4 Pro is totally usable for prototyping and concept work. The Metal acceleration implementation is clean — not a hack.”
“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.”
“Five minutes per mesh is 10x slower than CUDA on a decent GPU, and the output quality is only as good as the input photo and the model's training distribution. RMBG-2.0 has commercial licensing restrictions that many won't notice until they're already dependent on it. Useful for hobbyists; proceed cautiously for production.”
“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.”
“Every object in the physical world is a potential 3D asset — just photograph it. As ports like this land on consumer hardware, we're approaching a world where any creator can populate 3D environments from their phone camera. The 3D content bottleneck is dissolving faster than people realize.”
“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.”
“Photo to game-ready 3D mesh with PBR textures, no cloud, no subscription, runs on my MacBook. I've been waiting for this workflow for years. Even at 5 minutes a model, this transforms how I source assets for 3D scenes and AR projects. Absolute ship for creative work.”
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