vggt-mps: VGGT 3D Vision Agent optimized for Apple Silicon with Metal Performance Shaders

by jmanhype · MCP Server · ★ 93

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install vggt-mps

git clone https://github.com/jmanhype/vggt-mps.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 71/100

None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

3d-reconstructionapple-siliconclaude-desktopcomputer-visiondepth-estimationm1m2m3macosmcp

Quick Facts

Stars93
Forks10
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score71/100
Open Issues8
Last Updated2026-03-25
Created2025-09-18
Platformsclaude-code, mcp, python
Est. Tokens~2539k

About vggt-mps

vggt-mps Port of Facebook Research's VGGT (Visual Geometry Grounded Transformer) to Apple Silicon via PyTorch's MPS backend. Takes single or multi-view images and produces depth maps, camera poses, and 3D point clouds. What it produces Given N input images, VGGT predicts: Architecture The upstream VGGT model is a 1B-parameter transformer trained on multi-view geometry tasks.

Compatible Skills

These tools work well together with vggt-mps for enhanced workflows:

  • unsloth-buddy — semantic(0.32)+complementary+rare_topics+same_lang+similar_pop+shared_platform (66%)
  • Toolio — semantic(0.28)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • ChatSim — semantic(0.23)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • PyVision — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • table-transformer — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (55%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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