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remove_background

Read-onlyIdempotent

Remove image background using AI (U2-Net). Returns RGBA PNG/WebP with transparent background. Perfect for product photos, portraits, and design assets. FREE. (FREE)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "image": "<image>"
    },
    "name": "remove_background"
  }
}

Input Schema

Name	Required	Description	Default
`image`	Yes	Base64-encoded PNG/JPEG image
`output_format`	No	Output format	png

Schema Changelog

Changes observed during successful MCP inspections.

First observedMar 8, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description adds value by disclosed the return format (RGBA PNG/WebP). No contradictions; the redundant 'FREE' text doesn't affect behavioral transparency.

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

Conciseness3/5

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

The description is mostly succinct but includes redundant 'FREE' and '(FREE)' text that wastes space and doesn't aid an AI agent. The structure is a bit fragmented, so it doesn't earn a 4.

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 simple tool with two params and strong annotations, the description adequately covers the operation, return format, and use cases. It lacks mention of size limits or edge cases, but that's not critical for a straightforward image processing tool.

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 covers 100% of parameters with descriptions for both image and output_format. The description only reiterates the output formats already enumerated in the schema, so it adds no meaningful beyond schema.

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?

Description uses a specific verb ('Remove') and resource ('image background'), names the AI method (U2-Net), and specifies output format (RGBA PNG/WebP). This clearly distinguishes it from sibling tools like resize_image or convert_color_profile.

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?

Provides clear use cases ('Perfect for product photos, portraits, and design assets') but does not explicitly state when not to use or name alternatives. Context is sufficient for basic selection.

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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