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Remove the background from an image

background_remove

Remove an image background and save the cutout as a transparent PNG locally, with no uploads or API calls. Choose fast, best, portrait, or anime quality.

Instructions

Cuts out the subject and saves a transparent PNG, fully on this computer with rembg and BiRefNet models (no upload, no API). quality: fast (BiRefNet lite, default), best (BiRefNet general, slower, ~1 GB model on first use), portrait (people), anime. The first run downloads the model once. Needs rembg: uv tool install "rembg[cpu,cli]".

Input Schema

NameRequiredDescriptionDefault
qualityNofast
overwriteNo
input_pathYes
output_pathNoDefault: <name>-cutout.png next to the input

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.1

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 burden and does substantial work: it discloses local-only processing with no upload or API, the one-time model download on first run, and the exact dependency install command. It omits what happens when the target file already exists and whether the input file is ever modified, which matters for a writing tool.

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

Conciseness4/5

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

Front-loaded with the outcome, then the presets, then the environment caveat; nearly every clause earns its place. The install command is useful but sits slightly awkwardly at the tail.

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

Completeness3/5

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

There is no output schema, so the description must say what comes back, and it only implies a file is written rather than stating whether a path is returned. Combined with the silent `overwrite` parameter, an agent knows the intent but not the failure and return contract.

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 25%, so the description must compensate and does so well for `quality`, mapping each enum value to a model, speed cost, and use case. However, `overwrite` is undocumented in both schema and description, leaving the agent to guess whether false means error or skip, which is the riskiest parameter here.

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?

States a specific verb and resource: cuts out the subject and saves a transparent PNG, entirely on this machine. The operation is distinct from every sibling listed (media_optimize, media_cleanup, image_generate all do something else), so an agent can select it without ambiguity.

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

Usage Guidelines4/5

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

The quality presets are explained with the conditions that select them (fast = default, best = slower with a ~1 GB model on first use, portrait = people, anime), which is real selection guidance. It stops short of stating when to prefer this tool over a sibling like media_optimize, and gives no exclusion for non-photographic inputs.

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