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runapi-ai

@runapi.ai/flux-kontext-mcp

by runapi-ai

text_to_image

Generate images from text prompts using Flux Kontext models. Returns task ID, status, and output URLs for the generated images.

Instructions

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
watermarkNo
aspect_ratioNo
callback_urlNo
output_formatNo
safety_toleranceNo
source_image_urlNo
enable_translationNo
enable_prompt_expansionNo
waitNoPoll until the task reaches a terminal status.
timeout_msNo
poll_interval_msNo
modelNoRunAPI model slug for this model line.
Behavior2/5

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

Without annotations, the description carries full burden. It mentions the tool creates a task and returns task id, status, and output URLs, but does not disclose key behavioral traits such as asynchronicity, auth requirements, rate limits, or that the 'wait' parameter defaults to true for polling. Significant gaps remain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence, but it is too brief for a tool with 13 parameters. While it avoids verbosity, it sacrifices necessary detail, making it under-specified.

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 complexity (13 parameters, no output schema, no annotations), the description is incomplete. It does not explain the Flux Kontext domain, how to use the returned task id with sibling tools, or what the output URLs represent. The description leaves many operational questions unanswered.

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

Parameters2/5

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

Schema description coverage is only 15% (only 'wait' and 'model' have descriptions). The description itself adds no parameter semantics beyond the schema. For a tool with 13 parameters, this is insufficient; key parameters like 'prompt', 'aspect_ratio', and 'output_format' are left unexplained.

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

Purpose4/5

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

Description clearly states the tool creates a Flux Kontext task for text-to-image generation, which distinguishes it from siblings like check_pricing and get_task. The verb 'Create' and resource specification are specific and not a tautology.

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 on when to use this tool versus alternatives. The description implies it's for generating images from text, but lacks when-not conditions or exclusions. The sibling tools suggest different purposes, but this is not articulated.

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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