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Remove image background

remove_image_background

Removes an image's background, optionally replacing it with another supplied image. Costs 5 credits. Starts a background job; returns a project id for wait_for_image_project.

Input Schema

NameRequiredDescriptionDefault
nameNoGive your image a custom name for easy identification.Background Remover - dateTime
assetsYesProvide the assets for background removal

Output Schema

NameRequiredDescriptionDefault
idYesUnique ID of the image. Use it with the [Get image Project API](https://docs.magichour.ai/api-reference/image-projects/get-image-details) to fetch status and downloads.
credits_chargedYesThe amount of credits deducted from your account to generate the image. We charge credits right when the request is made. If an error occurred while generating the image(s), credits will be refunded and this field will be updated to include the refund.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true), and the description adds genuinely new behavioral facts: a 5-credit cost and asynchronous job semantics with a follow-up wait tool. It omits what happens on failure or whether credits are refunded, but the value-add over annotations is substantial.

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 short sentences in a tight purpose → cost → next-step order. Every sentence carries an independent, actionable fact with 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?

With an output schema present, the description needn't explain return values, and cost plus the async handoff to wait_for_image_project are the facts an agent most needs. The description is nearly sufficient, though it could note the required image_file_path vs optional background image relationship more explicitly.

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 description coverage is 100%, so both nested parameters are already fully documented including accepted URL/file_path formats. The phrase "optionally replacing it with another supplied image" usefully signals that background_image_file_path is not required, but adds nothing about format or sizing beyond what the schema states.

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

Purpose4/5

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

The description names a specific verb and resource ("Removes an image's background") and adds the optional replacement behavior, which is more than a restatement of the title. It does not explicitly distinguish itself from adjacent siblings such as edit_image or generate_image, so an agent must infer the boundary.

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?

It gives clear operational context — this kicks off an asynchronous job and hands back a project id for wait_for_image_project — which effectively tells the agent the correct follow-up call. It stops short of stating when to prefer this over generic image-editing siblings or any preconditions on input assets.

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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