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runapi-ai

RunAPI Midjourney MCP Server

by runapi-ai

image_to_prompt

Converts a source image URL into a Midjourney text prompt, returning the generated prompt synchronously.

Instructions

Run a synchronous Midjourney operation on RunAPI (image to prompt). Returns the operation result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_image_urlYesDeclared type: string.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.4.0
    • changedInput schema / additionalProperties
      Previous value: -falseNew value: +{}
    • addedInput schema / properties / source_image_url / description
      Added value: +"Declared type: string."
  2. First observedv0.3.0

TDQS

C2.8/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden, and it does disclose one genuine trait: the operation is synchronous, implying a blocking call that returns results directly rather than a task handle. Beyond that, it says nothing about permissions, cost, rate limits, or failure modes, and 'Returns the operation result' is circular, so the disclosure is thin.

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?

Two short sentences, front-loaded with the platform and mode, with no filler or repetition. It is efficient, though its brevity reflects under-specification rather than disciplined compression.

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?

This wraps an external Midjourney API call with no annotations and no output schema, so the description should explain the return shape, auth requirements, and limitations. Instead it gives an empty 'Returns the operation result' without saying whether the result is a prompt string, a task object, or a URL, leaving the agent under-informed for invocation.

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 reported at 100%, so the baseline of 3 applies even though the description adds no parameter detail. The single schema description ('Declared type: string') is largely uninformative, but the parameter name source_image_url is self-explanatory, so nothing critical is lost.

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

Purpose3/5

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

The description names a platform and a mode ('Run a synchronous Midjourney operation on RunAPI') plus the parenthetical '(image to prompt)', which mostly restates the tool name rather than explaining the action. It never says what 'image to prompt' actually produces (a text prompt derived from a source image) or how it differs from siblings like text_to_image or shorten_prompt. The purpose is inferable but only vaguely conveyed.

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?

There is no when-to-use guidance, no statement of prerequisites (API credentials, image constraints), and no routing against alternatives such as text_to_image, edit_image, or image_to_video. The agent must guess which tool applies to a given user intent.

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