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mcpGetImage

mcpGetImage

by raulisai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

generate_candy_image

Generates a candy product image using OpenAI, then removes the white background to produce a transparent WebP.

Instructions

Generate a candy image with OpenAI, then remove its white background.

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": {
      "request": "<request>"
    },
    "name": "generate_candy_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
styleNofotografia de producto premium
requestYes
compositionNoproducto centrado, vista tres cuartos
output_nameNo
extra_detailsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the two main operations but omits critical details such as output format, whether the removal is automatic, potential side effects on the generated image, or any limitations. This leaves the agent under-informed about the tool's runtime behavior.

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?

The description is a single, concise sentence that front-loads the core action. It avoids wordiness and includes no redundant information, achieving optimal efficiency.

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

Completeness2/5

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

Given the tool's moderate complexity (5 parameters, no annotations) and zero schema description coverage, the one-line description is insufficient for an agent to invoke it correctly. The presence of an output schema does not compensate for missing parameter semantics and usage context.

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

Parameters1/5

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

Schema description coverage is 0%, and the description provides zero explanation of the parameters (style, request, composition, output_name, extra_details). The description must compensate for the lack of schema documentation but fails entirely, leaving agents without clues to what each parameter means.

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 clearly states a two-step action: generate a candy image using OpenAI and then remove its white background. This is a specific verb-plus-resource statement that distinguishes the tool from sibling tools like 'remove_background' and 'refine_candy_prompt' by combining both generation and background removal.

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

Usage Guidelines2/5

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

No explicit guidance is provided on when to use this tool versus alternatives. While the description implies a use case (generating a new candy image with a cleaned background), it does not mention that users needing only background removal should use 'remove_background' instead, nor does it outline any prerequisites or exclusions.

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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