Apple Image Playground MCP Server
mcp-apple-image-playground
npm
v1.1.3
Published by vakandi — 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.
AI image generation MCP server via Apple Image Playground — on-device styles (animation, illustration, sketch) + ChatGPT external styles (oil painting, watercolor, vector, anime, print). 17 tools, 40+ social presets, zero API keys. Plug-and-play for Claud
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 − 1.2 = 99. What the published surface and source actually contain:
| Points | What was found | Category |
|---|---|---|
| −1.2 | Package runs install-time scripts MTC-SUP-010 | supply-chain |
2. Client adoption risk — 99 − 7 = 92. 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 4
high Shell/command execution in server code (apple_intelligence/engines.py)MTC-SRC-002
In the server's implementation (`apple_intelligence/engines.py:128`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: try: proc = subprocess.run( ["open", "-a", str(_APP_BUNDLE_PATH)], stdin=subprocess.
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server apple_intelligence/engines.py
high Shell/command execution in server code (apple_intelligence/server.py)MTC-SRC-002
In the server's implementation (`apple_intelligence/server.py:55`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: cess shortcuts_ok = subprocess.run( ["shortcuts", "list"], capture_output=True, text=True, timeout=5, ).
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server apple_intelligence/server.py
low Shell/command execution in packaging/dev tooling (postinstall.js)MTC-SRC-002
In a packaging/dev/install script (shipped, but not the server runtime) (`postinstall.js:7`): Spawning a shell/process is command-execution capability; with unsanitized tool input it is command injection / RCE. This is read from the code itself — not from the tool description — so a poisoned server cannot hide it behind honest-looking metadata.
Evidence: { execSync } = require("child_process"); const path = require("path"); const fs = require("fs"); const ROOT = __dirname
Fix: Review this call path: confirm it never receives unsanitized tool input, constrain it, or remove it. Treat a server whose code reaches these sinks as high-capability regardless of what its tools claim.
Location: server postinstall.js
low Package runs install-time scripts (postinstall)MTC-SUP-010
"mcp-apple-image-playground" executes postinstall script(s) at install time. An install hook runs at install time; most are routine build/setup, but review what it does before trusting it.
Evidence: node postinstall.js
Fix: Review the scripts; install with --ignore-scripts where possible and vet what they do.
Location: package mcp-apple-image-playground
Tools 16
Each tool and what it can reach — statically extracted from the published source.
add_text_overlayno sensitive capabilityadd_watermarkno sensitive capabilityapply_filterno sensitive capabilitycreate_gradientno sensitive capabilitycreate_text_postno sensitive capabilitycrop_imageno sensitive capabilitygenerate_batchno sensitive capabilitygenerate_bundleno sensitive capabilitygenerate_imageno sensitive capabilitygenerate_social_packno sensitive capability
Show 6 more tools ↓
list_bundlesno sensitive capabilitylist_enginesno sensitive capabilitylist_presetsno sensitive capabilitylist_stylesno sensitive capabilityresize_imageno sensitive capabilitysmart_cropno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (16 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 |
|---|---|---|---|---|
v1.1.3 latest |
A 92/100 | 4 | 1.13.0 | 2026-09-08 |
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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