Brandkity MCP Server
@brandkity/mcp
npm
v1.4.3
Published by @brandkity — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
BrandKity MCP Server — Create and manage brand kits from AI agents
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 − 7 = 93. 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 |
|---|---|
| −6 | capability blast radius (high) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
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 1
high Sensitive-source and external-sink co-existMTC-FLOW-004
Tools that read sensitive data ([list_files]) and tools that can send data out ([upload_file]) are exposed together. An agent can move private data to the sink.
Evidence: sources [list_files] → sinks [upload_file]
Fix: Keep secret-reading and egress capabilities on separate, separately-approved servers.
Location: flow list_files → upload_file
Tools 22
Each tool and what it can reach — statically extracted from the published source.
list_filesreads sensitive dataupload_filenetwork egressadd_blockno sensitive capabilityadd_colorsno sensitive capabilityadd_typographyno sensitive capabilitycreate_kitno sensitive capabilitydelete_blockno sensitive capabilityensure_blockno sensitive capabilityget_kitno sensitive capabilityget_workspaceno sensitive capability
Show 12 more tools ↓
list_blocksno sensitive capabilitylist_kitsno sensitive capabilitypublish_kitno sensitive capabilityset_block_noteno sensitive capabilityset_brand_storyno sensitive capabilityunpublish_kitno sensitive capabilityupdate_blockno sensitive capabilityupdate_kitno sensitive capabilityupload_assetno sensitive capabilityupload_assets_batchno sensitive capabilityupload_cover_imageno sensitive capabilityupload_kit_logono sensitive capability
Toxic flows 1
Cross-tool combinations that form a data-exfiltration primitive (untrusted input → sensitive source → external sink).
What this scan could not see
- Tools were statically extracted from the published source (22 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 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.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v1.4.3 latest |
A 93/100 | 1 | 1.13.0 | 2026-09-07 |
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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