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apexapi-mcp

apexapi-mcp

Official
by apexapi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Generate an image

generate_image

Generate an image from a text description and get a hosted URL. Review image models and costs using list_models.

Instructions

Generate an image from a text prompt. Returns a URL. Use list_models with type=image for available models and prices.

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": {
      "model": "<model>",
      "prompt": "<prompt>"
    },
    "name": "generate_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
sizeNoWIDTHxHEIGHT, default 1024x1024
modelYesImage model slug, e.g. openai/dall-e-3
promptYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.7/5.0
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 only mentions that it returns a URL, but omits important details such as whether the operation is synchronous, whether it consumes credits (given list_models mentions prices), or what happens on failure. This is a significant gap for a generation tool.

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 exactly two sentences, front-loaded with the core function and output, followed by a useful prerequisite note. Every sentence earns its place with no redundancy or filler.

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?

For a simple 3-parameter tool with no output schema, the description covers the basics: what it does, its output format, and how to find models. However, it leaves unresolved questions about cost, synchronous vs. asynchronous behavior (especially given the check_job sibling), and error handling, making it adequate but not complete.

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 67%, covering size and model but not prompt. The description adds meaning by explaining that the prompt is a text prompt for image generation and directs the user to list_models for available model slugs, which partially compensates for the missing prompt description. It does not add syntax or format details beyond what the schema provides.

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 the tool's function with a specific verb and resource: 'Generate an image from a text prompt. Returns a URL.' This distinguishes it from siblings like generate_speech and chat, leaving no ambiguity about what the tool does.

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 provides clear usage context by telling the user to 'Use list_models with type=image for available models and prices,' which is a prerequisite for using this tool correctly. However, it does not explicitly mention when not to use this tool or name alternative image generation tools, but none exist among the siblings.

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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