Furniture Designer MCP Server

furniture-designer-mcp PyPI v0.1.3

Published by an unidentified publisher — no publish provenance and no public repository, so the publisher could not be verified and the source cannot be independently located.

Trust grade
A
98/100
Last scanned get badge →
Trust
A · 98/100
Adoption risk for you: the threat score, then adjusted down for blast radius, publisher verification and how much the scan could see. Deterministic; every point is auditable.
Capability
Minimal
Blast radius if it went rogue — what the server’s tools could reach. Independent of trust.
Coverage
Source
How much the scan could actually inspect. Shallow coverage is stated, never hidden.
A Why this grade threat 100 − adoption risk = 98/100

The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.

1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:

The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.

2. Client adoption risk — 100 − 2 = 98. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:

PointsAdoption-risk factor
−2 publisher verification (unlinked) — no provenance/repo link, but the shipped source was fully read

Capability observations and info notes are shown under Findings but never scored. Open any row's finding below for the file, line and evidence behind a deduction.

Findings 0

✓ No findings. The scan raised nothing on this surface — see Coverage for how deep it could look.

Tools 25

Each tool and what it can reach — statically extracted from the published source.

  • build_3d_modelno sensitive capability
  • build_cut_diagramno sensitive capability
  • build_exploded_viewno sensitive capability
  • build_import_scriptno sensitive capability
  • build_specno sensitive capability
  • build_techdrawno sensitive capability
  • create_designno sensitive capability
  • design_furnitureno sensitive capability
  • generate_bomno sensitive capability
  • generate_full_reportno sensitive capability
Show 15 more tools ↓
  • get_assembly_specsno sensitive capability
  • get_assembly_stepsno sensitive capability
  • get_design_contextno sensitive capability
  • get_hardware_catalogno sensitive capability
  • get_material_specsno sensitive capability
  • get_section_mapno sensitive capability
  • get_standardsno sensitive capability
  • get_structural_rulesno sensitive capability
  • list_designsno sensitive capability
  • optimize_cutsno sensitive capability
  • parse_freecad_importno sensitive capability
  • reload_engineno sensitive capability
  • start_design_serverno sensitive capability
  • update_design_reportno sensitive capability
  • validate_structureno sensitive capability

What this scan could not see

Versions 1

Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.

VersionScoreFindingsEngineScanned
v0.1.3 latest A 98/100 0 1.9.0 2026-07-23

Embed this score

Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.

MCP Trust Score: A · 98/100
Markdown (GitHub README)
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Verify this score yourself

The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.

npx mcptrustchecker scan furniture-designer-mcp --online --registry pypi

Use the free API → How scoring works

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