ifc-lite: Parse, view, query, edit, validate and export building models

by LTplus-AG · MCP Server · ★ 459

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

How to install ifc-lite

npx create-ifc-lite my-viewer --template react
npm install @ifc-lite/parser @ifc-lite/geometry @ifc-lite/renderer

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 67/100

Flagged: install step in a code block runs a script from an untrusted host. Scanned against 42 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.

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Quick Facts

Stars459
Forks122
LanguageTypeScript
CategoryMCP Server
LicenseMPL-2.0
Quality Score67/100
Open Issues55
Last Updated2026-11-05
Created2026-01-10
Platformsbrowser, cli, mcp, node
Est. Tokens~16k

About ifc-lite

Open, view, and work with IFC files. Right in the browser. IFClite Parse, view, query, edit, and export IFC files in the browser. Rust + WASM core, WebGPU rendering

Compatible Skills

These tools work well together with ifc-lite for enhanced workflows:

  • Claw3D — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (55%)
  • header — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)
  • circuitiny — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • inngest — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 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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