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runapi-ai

Ideogram V3 MCP Server

by runapi-ai

text_to_image

Generate images from text prompts using Ideogram V3. Submit a prompt and receive a task ID, status, and output URLs.

Instructions

Create a Ideogram V3 task on RunAPI (text to image). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
styleNo
promptNo
timeout_msNo
aspect_ratioNo
callback_urlNo
output_countNo
negative_promptNo
rendering_speedNo
poll_interval_msNo
reference_image_urlsNo
enable_prompt_expansionNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a task id, status, and output URLs, but it omits behavioral details such as whether the task is asynchronous, whether the 'wait' parameter controls polling, authentication requirements, or potential side effects. This is minimal disclosure.

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 two sentences, front-loaded with the core action, and contains no redundant information. Every word adds value.

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

Completeness1/5

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

With 14 parameters, no output schema, and no annotations, the description provides only a basic purpose. It does not explain how to construct a valid request, what the response includes beyond IDs and URLs, or the effects of optional parameters. This is critically incomplete for a tool with this complexity.

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 only 14% (2 of 14 parameters have descriptions). The description adds no parameter-level guidance, failing to explain the meaning or importance of parameters like prompt, aspect_ratio, or style. It does not compensate for the low schema coverage.

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: 'Create a Ideogram V3 task on RunAPI (text to image)' and immediately notes the return value: 'Returns a task id, status, and output URLs.' This distinguishes it from sibling tools like edit_image or remix_image, which imply different operations.

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

Usage Guidelines3/5

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

The description implies usage for text-to-image generation (as opposed to editing/reframing), but it does not explicitly state when to use this tool versus alternatives, nor does it list any exclusions or prerequisites. No guidance is given about scenarios where another sibling would be more appropriate.

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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