GPT Image MCP Server

generate_batch

Generate multiple images at once using distinct parameters per request, enabling batch production with controlled concurrency.

Instructions

Generate multiple images at once with different parameters.

Args: requests: List of image generation requests (each with prompt, content_type, etc.) max_concurrent: Maximum number of concurrent generations (1-10)

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": {
      "requests": "<requests>"
    },
    "name": "generate_batch"
  }
}

Input Schema

Name	Required	Description	Default
`requests`	Yes
`max_concurrent`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Aug 7, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions the concurrency limit range (1-10) but does not describe error handling, return behavior, or other side effects. Some context is provided, but deeper traits are missing.

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 concise and front-loaded with the core purpose. The Args block efficiently documents parameters without redundancy or irrelevant details.

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?

The tool has an output schema and parameters are well explained, but the description lacks usage guidance relative to siblings and does not address potential batch size limits or failure behavior. It covers the essentials but leaves gaps for an agent to fully understand when to use this tool.

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

Parameters5/5

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

The input schema lacks meaningful descriptions (0% coverage), but the description explicitly explains both parameters: requests (list of generation requests) and max_concurrent (concurrency range 1-10). This adds significant value beyond the schema's type and title information.

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 a specific action ('Generate multiple images at once') and distinguishes it from single-image generation by its batch nature. It identifies the resource (images) and the differentiation from sibling tools like generate_image.

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 batch generation with different parameters, but it does not explicitly state when to prefer this tool over alternatives like generate_image. No exclusions or alternative references are provided.

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

Deploy Server