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fvtt-mcp-artificer

by Txpple
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TypeScript
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cutout-image

Cut the background off a token image to transparent alpha and center it for Foundry VTT, with preview and safe fallback.

Instructions

Knock the background off a token image to real alpha and deliver it centred on a 512 square so Foundry scale 1.0 is right. Writes a magenta-composited *_preview.png beside it: READ THAT before trusting the edge. Returns coverage and residual-key numbers; a cut outside sane coverage falls back to the rembg AI matte automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoSquare canvas edge; default 512 (Foundry scale 1.0). 0 keeps the source canvas.
trimNoTighten to the subject before fitting (default true); false letterboxes as-is.
colorNoChroma key colour: "green", "magenta", "blue", or #RRGGBB. Omit to sample the corners.
erodeNoShrink the matte N px to eat a fringe.
methodNoauto (default): chroma if the plate is a flat key colour, with a rembg fallback when the cut fails verification. chroma: flat green/blue/magenta/solid plates, instant. rembg: AI matte for busy backgrounds, hair, and soft edges (first use downloads a ~176 MB model).
outputNoAbsolute output path (.png). Default: next to the source as <name>-cut.png.
padPctNoTransparent margin, % of the edge (4).
keepShadowNochroma only: keep a cast shadow on the plate.
sourceImageYesAbsolute path of the image to cut (PNG/JPEG/WebP).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.0

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does well: it discloses side-effect preview file creation, instructs the user to verify edges, mentions returned coverage/residual-key numbers, and reveals automatic fallback to rembg. It does not mention overwrite behavior or other filesystem side effects beyond the preview and output, but the core behavioral traits are covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each earning its place: purpose and canvas behavior, preview verification warning, and output/fallback behavior. It is front-loaded and contains no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter tool with no annotations and no output schema, the description is unusually complete: it covers processing, output artifact, verification workflow, fallback behavior, and key return values. The remaining gaps are the lack of exact 'sane coverage' thresholds and a precise response shape.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline of 3 applies. The description reinforces the purpose of size and output but adds no extra parameter-level detail beyond what the input schema already documents.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it removes the background from a token image and produces a transparent cutout centered on a 512-square canvas. This clearly distinguishes it from image generation, general editing, and status-checking siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The intended use is implied clearly through 'token image' and 'Foundry scale 1.0', and the method parameter guidance explains when to prefer chroma versus rembg. However, it never names alternatives or says when not to use this tool versus generate-image or edit-image.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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