mcp-xmorf

xmorf_generate_image

Generate an image from a text description using AI. Specify a prompt, choose an OpenAI model and dimensions, and optionally save the result to a file.

Instructions

Generate an image from a text description using AI

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": "xmorf_generate_image"
  }
}

Input Schema

Name	Required	Description
`prompt`	Yes	Text description of the image to generate, e.g. 'A futuristic city at sunset, cyberpunk style'
`model`	No	OpenAI model to use (default: dall-e-2)
`size`	No	Image dimensions, e.g. 1024x1024 (default: 1024x1024)
`outputPath`	No	Save result to this file path instead of returning base64

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.2May 29, 2026

TDQS

B3/5.0

Behavior2/5

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

No annotations provided. Description only says 'using AI' without disclosing specifics like API provider (OpenAI), authentication, rate limits, or output handling. Behavioral traits such as cost implications or generation time 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.

Conciseness3/5

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

Description is a single sentence, very concise. However, it lacks structured details and is arguably too brief for a tool with 4 parameters. Could be improved with bullet points or additional context.

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?

With 4 parameters, no output schema, and no annotations, the description is insufficient. It omits details like output format (base64 or file), authentication, model defaults, and error handling. The tool's complexity demands more context.

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% (all 4 parameters documented). The description adds no extra meaning beyond the schema. Baseline score is appropriate.

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?

Description clearly states 'Generate an image from a text description using AI'. It specifies the action (generate), resource (image), and input (text description). Siblings (xmorf_edit_image, xmorf_list_models) have different purposes, so this tool is well-differentiated.

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 guidance on when to use this tool versus siblings (e.g., when to generate vs edit vs list models). No when-not-to-use or prerequisite information. The description is a generic statement without usage context.

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

Deploy Server