Framesmith MCP Server
framesmith
npm
v2.2.0
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.
MCP server that gives any AI assistant a visual design canvas
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:
| Points | Adoption-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
Tools 60
Each tool and what it can reach — statically extracted from the published source.
apply_presetno sensitive capabilityapply_structureno sensitive capabilitybatch_designno sensitive capabilitycanvas_add_variantno sensitive capabilitycanvas_archiveno sensitive capabilitycanvas_autofixno sensitive capabilitycanvas_bindno sensitive capabilitycanvas_check_driftno sensitive capabilitycanvas_createno sensitive capabilitycanvas_deleteno sensitive capability
Show 50 more tools ↓
canvas_diffno sensitive capabilitycanvas_evaluateno sensitive capabilitycanvas_import_htmlno sensitive capabilitycanvas_import_urlno sensitive capabilitycanvas_listno sensitive capabilitycanvas_moveno sensitive capabilitycanvas_reviseno sensitive capabilitycanvas_set_genreno sensitive capabilitycanvas_stressno sensitive capabilitycanvas_sync_from_urlno sensitive capabilitycanvas_unarchiveno sensitive capabilitycanvas_versionno sensitive capabilitycopy_nodesno sensitive capabilitycreate_componentno sensitive capabilityexportno sensitive capabilityfind_nodesno sensitive capabilitygenerate_color_systemno sensitive capabilitygenerate_design_systemno sensitive capabilitygenerate_scaleno sensitive capabilityget_feedbackno sensitive capabilityget_fontsno sensitive capabilityget_variablesno sensitive capabilityimport_design_mdno sensitive capabilityinitno sensitive capabilitylist_presetsno sensitive capabilitylist_structuresno sensitive capabilityproject_apply_presetno sensitive capabilityproject_createno sensitive capabilityproject_deleteno sensitive capabilityproject_evaluateno sensitive capabilityproject_get_design_systemno sensitive capabilityproject_listno sensitive capabilityproject_renameno sensitive capabilityproject_set_design_systemno sensitive capabilityread_nodesno sensitive capabilityreplace_matching_propertiesno sensitive capabilityresolve_feedbackno sensitive capabilityscreenshotno sensitive capabilityscreenshot_responsiveno sensitive capabilityset_fontsno sensitive capabilityset_variablesno sensitive capabilitysnapshot_layoutno sensitive capabilityviewer_urlno sensitive capabilityworkspace_apply_presetno sensitive capabilityworkspace_createno sensitive capabilityworkspace_deleteno sensitive capabilityworkspace_get_design_systemno sensitive capabilityworkspace_listno sensitive capabilityworkspace_renameno sensitive capabilityworkspace_set_design_systemno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (60 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 4
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.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v2.2.0 latest |
A 98/100 | 0 | 1.13.0 | 2026-09-09 |
v2.0.0 |
A 98/100 | 0 | 1.13.0 | 2026-09-01 |
v1.10.0 |
A 98/100 | 0 | 1.12.1 | 2026-08-09 |
v1.9.0 |
A 98/100 | 0 | 1.12.1 | 2026-07-27 |
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.
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.
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