apple-image-mcp (vakandi/mcp-apple-image-playground) is an MCP server listed on the M8ven Trust Index. It scores 48 out of 100, grade D. It declares 16 tools. No publisher has claimed this listing.

D
Caution
48/100

apple-image-mcp

On-device AI image generation for macOS with 17 tools and zero API keys, combining Apple Intelligence and Pollinations for stylized and photorealistic images, auto-cropping for 40+ social media platforms.

Caution. Specific findings reduced this grade. They are listed on the page. Grades reflect the full trust pyramid: code, verification depth, and reputation. New projects cap at C until adoption is earned.

How we verified

⚡ Live Monitored: not connected

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Who stands behind it

vakandi

Source: Glama

Is this your MCP?

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Install from

The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.

// key findings
⚠️
Tool descriptions don’t match what handlers do
1 tool describes read intent but its handler mutates — list_engines (line 55: shortcuts_ok = subprocess.run()
No credential exfiltration, no sensitive file access, no obfuscation
Static analysis found nothing flowing your secrets to unexpected places.
Open source with a license and README
Anyone can audit the code, the license is declared, and the publisher documents what it does.
// tools this server exposes16 tools

These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.

list_engines

List available image generation engines. Apple Image Playground runs fully on-device via Shortcuts.app — no API keys, no cloud calls.

list_presets

List all 40+ social media / blog / web output size presets with dimensions.

list_bundles

List predefined bundles — groups of presets for common use cases.

list_styles

List all available Apple Image Playground styles from the ImagePlayground API.

generate_image

Generate an image using Apple Image Playground via Shortcuts.app. Fully on-device — no API keys, no cloud calls.

generate_social_pack

Generate one master image via Image Playground, then crop to multiple platform sizes.

generate_bundle

Generate images for a predefined bundle (e.g. "full_social", "blog_set"). Use list_bundles() to see available bundles.

generate_batch

Generate images for multiple prompts at once. Each prompt gets its own master image + optional platform crops.

add_text_overlay

Overlay text on an image — for quotes, CTAs, headlines, announcements. Adds semi-transparent background behind text for readability.

add_watermark

Add a text watermark to an image for brand protection.

create_gradient

Generate a gradient background image. Useful as a base for text posts or social media content that doesn't need a photo.

create_text_post

Create a ready-to-post text image (quote, announcement, tip). Generates a gradient or solid background with styled text. Perfect for Instagram carousel text slides or Twitter text posts.

apply_filter

Apply a visual filter to an image via PIL. Available: blur, sharpen, brightness, contrast, saturation, sepia, noir.

smart_crop

Crop an image to exact dimensions using center-crop.

crop_image

Take an existing image and crop it to multiple platform sizes. No generation — just reformatting an image you already have.

resize_image

Resize an image. Specify width/height or scale factor.

// quality suggestions

Tool annotations

No tools have read-only/destructive annotations

Add readOnlyHint or destructiveHint annotations to every tool so hosts can warn users before invoking.

All four hints declared on every tool

16/16 tools missing one or more hints — list_engines (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); list_presets (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint); list_bundles (missing: readOnlyHint, destructiveHint, idempotentHint, openWorldHint), +13 more. OpenAI's directory rejects tools where any of the four hints are missing or non-boolean.

For every tool, set all four hints (readOnlyHint, destructiveHint, idempotentHint, openWorldHint) to explicit true/false values that match the handler’s actual behaviour.

Descriptions match behaviour

1 tool describes read intent but its handler mutates — list_engines (line 55: shortcuts_ok = subprocess.run()

Rename the tool, rewrite the description, or move the side-effect into a separate clearly-named tool.

Tool inputs are validated

12/16 tool handlers declare input schemas (75%)

Declare an inputSchema with zod/joi/yup on every tool definition.

Tool handlers catch errors

10/16 tool handlers wrap calls in try/catch (63%)

Wrap each tool handler body in try/catch and return a structured error response.

Tests exist

No test files found

Add tests that exercise each declared tool.

No arbitrary install scripts

Has postinstall/preinstall script — runs arbitrary code on npm install

Remove postinstall/preinstall hooks unless they’re essential.

Tool description accuracy

list_engines: description implies read-only but handler writes/deletes/executes

Update tool descriptions to accurately reflect all capabilities — especially write, delete, or execute operations.

Claim the listing to review these findings one by one and send us a correction where you disagree, straight to the team. Claiming also means we tell you when the grade moves, and reach you first if we find anything urgent.

// full audit trail
The findings above are the summary. The full trail, every check we ran, each deduction, the network hosts observed and the dependency advisories, goes to verified publishers, along with an alert whenever a new one lands. Verified publishers can also review each finding and dispute it in one click. Publisher corrections have sharpened several of our checks this month, because the maintainer knows the codebase better than any scanner.
// improvement guidance — verified publishers only
We have 8 concrete improvements we can share with the publisher of this MCP. Each comes with specific guidance to raise the trust score.
// embed badge in your README
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commit: 617456afd0b549eb5658d312401282a8122f76c4
code hash: c4d5ab543e8389ca9c1d57290068ef312b3d9de8b7cd6d22fbcccb90f1c0365f
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