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RunAPI Qwen Image MCP Server

Official
by runapi-ai
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TypeScript
Remote

text_to_image

Generate images from text prompts using Qwen on RunAPI. Returns task ID, status, and output URLs for polling or asynchronous workflows.

Instructions

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoInteger seed for reproducible results. Declared type: integer.
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
promptYesImage generation prompt. Declared type: string.
timeout_msNo
aspect_ratioNoOutput aspect ratio. Declared type: string. Known values: "1:1", "3:4", "9:16", "4:3", "16:9".
callback_urlNoWebhook URL for asynchronous task updates. Declared type: string.
output_formatNoOutput image format. Declared type: string. Known values: "png", "jpeg".
poll_interval_msNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed14 schema fields changedv0.2.0
    • changedInput schema / additionalProperties
      Previous value: -falseNew value: +{}
    • changedInput schema / properties / aspect_ratio / description
      Previous value: -"Output aspect ratio."New value: +"Output aspect ratio. Declared type: string. Known values: \"1:1\", \"3:4\", \"9:16\", \"4:3\", \"16:9\"."
    • removedInput schema / properties / aspect_ratio / enum
      Removed value: -[
-  "1:1",
-  "3:4",
-  "9:16",
-  "4:3",
-  "16:9"
-]
    • changedInput schema / properties / callback_url / description
      Previous value: -"Webhook URL for asynchronous task updates."New value: +"Webhook URL for asynchronous task updates. Declared type: string."
    • removedInput schema / properties / model / enum
      Removed value: -[
-  "qwen-image-text-to-image"
-]
    • changedInput schema / properties / output_format / description
      Previous value: -"Output image format."New value: +"Output image format. Declared type: string. Known values: \"png\", \"jpeg\"."
    • removedInput schema / properties / output_format / enum
      Removed value: -[
-  "png",
-  "jpeg"
-]
    • addedInput schema / properties / poll_interval_ms / maximum
      Added value: +9007199254740991
    • changedInput schema / properties / prompt / description
      Previous value: -"Image generation prompt."New value: +"Image generation prompt. Declared type: string."
    • removedInput schema / properties / prompt / maxLength
      Removed value: -5000
    • removedInput schema / properties / prompt / minLength
      Removed value: -1
    • changedInput schema / properties / seed / description
      Previous value: -"Integer seed for reproducible results."New value: +"Integer seed for reproducible results. Declared type: integer."
    • changedInput schema / properties / seed / type
      Previous value: -"number"New value: +"integer"
    • addedInput schema / properties / timeout_ms / maximum
      Added value: +9007199254740991
  2. First observedv0.1.1

TDQS

B3.3/5.0
Behavior3/5

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 does disclose the async task model and the return payload ('task id, status, and output URLs'), which is valuable since there is no output schema, but it says nothing about the default polling behavior (wait=true), auth requirements, or rate limits.

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?

Two short sentences with the resource and endpoint front-loaded and zero wasted words. The parenthetical clarifies modality without bloat.

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 9-parameter async generation tool with no annotations and no output schema, the description covers the return shape but omits the critical behavioral detail that it polls by default via the wait parameter and can instead be webhook-driven via callback_url. Adequate but with clear gaps.

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 78%, so the schema already documents most parameters (aspect_ratio known values, output_format, seed, wait, callback_url). The description adds no parameter meaning at all, leaving the baseline of 3 appropriate.

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?

States a specific verb (Create) and resource (a Qwen Image task via text-to-image), which is enough to distinguish it from edit_image and remix_image among siblings. It does not explicitly name those alternatives, so it stops short of a 5.

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?

The parenthetical '(text to image)' implies the modality, but there is no explicit when-to-use guidance, no prerequisites, and no routing to sibling tools like edit_image for modifying an existing image. An agent must infer the boundary itself.

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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