z_ai_image_gen_mcp

generate_image

Generate an image from a text prompt and get the image URL directly.

Instructions

Generate an image synchronously from a text prompt. Returns the image URL directly. Use this for most image generation tasks.

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": {
      "prompt": "<prompt>"
    },
    "name": "generate_image"
  }
}

Input Schema

Name	Required	Description	Default
`size`	No	Image size (e.g., "1280x1280", "1568x1056")	1280x1280
`model`	No	Model to use for generation	glm-image
`prompt`	Yes	Text description of the image to generate
`quality`	No	Quality level: "hd" (more detailed, ~20s) or "standard" (faster, ~5-10s)
`user_id`	No	Unique end user ID for abuse prevention (6-128 characters)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Jul 30, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Discloses synchronous execution and direct URL return, which are key behavioral traits. However, with no annotations, the description carries the full burden and omits other relevant details such as authentication, rate limits, or cost implications.

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 sentences, highly concise and front-loaded with the core purpose. Every sentence adds value: first states the action and output, second recommends usage. No wasted words.

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?

Given 5 parameters and no output schema, the description is overly minimal. It covers the basic purpose but lacks details on error handling, parameter interdependencies, or example usage, leaving the agent with incomplete contextual understanding.

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 100% for all 5 parameters, so baseline is 3. The description does not add extra semantics beyond what the schema already provides for parameters like prompt, size, model, quality, and user_id.

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 'Generate an image synchronously from a text prompt' and 'Returns the image URL directly', which specifies the verb and resource. It implicitly distinguishes from the sibling generate_image_async by noting synchronous behavior, though it does not explicitly name the async alternative.

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?

Says 'Use this for most image generation tasks' to indicate when to use, but provides no guidance on when not to use or what alternatives exist (e.g., generate_image_async). No exclusions or context with siblings.

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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