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Remove background

remove_background

Removes a photo's background and returns the subject on a transparent PNG at the original size; pay 0.05 USDC per call on Base via x402.

Instructions

Removes the background from one photo and returns the subject on a transparent background as a PNG, at the photo's own size. Costs 0.05 USDC per call (real money) on Base, paid from the buyer's wallet over x402 after the buyer's spending limits are checked. Input: PNG, JPEG, WEBP, up to 8 MB, at most 4096 px. Give exactly one of image_url or image_path. Output: image/png, as a download link (and a file with save_to).

Input Schema

NameRequiredDescriptionDefault
save_toNoOptional local file path to save the result to (image/png).
image_urlNoA public https URL of the image.
overwriteNoReplace save_to if it exists. Default false.
image_pathNoA local image file to send (read by this server, sent base64).
allow_repeatNoBuy again even if the same request was bought in the last 10 minutes. Default false: the earlier result is returned and nothing is charged.
max_price_usdcNoOptional: refuse if Bacon asks more than this, in USDC.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only flag a non-idempotent open-world write; the description goes well beyond them by disclosing real monetary cost (0.05 USDC per call on Base), the x402 payment flow, and that spending limits are checked before charging. Combined with the explicit input limits (8 MB, 4096 px) and output format, an agent can predict cost and failure modes before invoking.

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 purpose, then cost, then constraints, then output — a sensible order with little waste. It is dense and slightly run-on in the input-limits clause, but nearly every sentence carries distinct information.

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 6-parameter tool with no output schema, the description covers purpose, cost, input constraints, mutual exclusivity, and return shape (download link plus optional save_to file). It omits only error/max_price behavior, which is a minor gap given the schema documents those parameters directly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline would be 3, but the description adds a cross-parameter constraint the schema cannot express: exactly one of image_url or image_path must be supplied. That constraint is meaningful and not repeated anywhere in the structured fields.

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 (removes the background from a photo) plus the exact output contract: subject on a transparent PNG at the photo's own size. That is distinguishable from every sibling (optimize_image, vectorize_image, image_palette), which transform differently and produce different artifacts.

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?

Gives concrete selection rules: 'Give exactly one of image_url or image_path' and accepted formats/size limits, which tells the agent when the tool is applicable. It does not explicitly route away from alternatives (e.g. optimize_image for compression) or state when not to call it, so it stops short of a 5.

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