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Image Generator MCP Server

by sammyl720
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

이미지 생성기 MCP 서버

이미지 프롬프트를 기반으로 이미지를 생성하는 mcp 서버

이는 OPENAI 의 dall-e-3 이미지 생성 모델을 사용하여 이미지 생성을 구현한 TypeScript 기반 MCP 서버입니다.

특징

도구

  • generate_image - 주어진 프롬프트에 대한 이미지 생성

    • prompt 필수 매개변수로 사용합니다.

    • 생성된 이미지를 데스크탑의 generated-images 디렉토리에 저장하기 위해 imageName 필수 매개변수로 사용합니다.

Related MCP server: Image Generator MCP Server

개발

종속성 설치:

지엑스피1

서버를 빌드하세요:

npm run build

자동 재빌드를 사용한 개발의 경우:

npm run watch

설치

Claude Desktop과 함께 사용하려면 서버 구성을 추가하세요.

MacOS의 경우: ~/Library/Application Support/Claude/claude_desktop_config.json Windows의 경우: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "command": "image-generator",
      "env": {
        "OPENAI_API_KEY": "<your-openai-api-key>"
    }
  }
}

<your-openai-api-key> 실제 OPENAI Api Key로 바꿔야 합니다.

디버깅

MCP 서버는 stdio를 통해 통신하므로 디버깅이 어려울 수 있습니다. 패키지 스크립트로 제공되는 MCP Inspector를 사용하는 것이 좋습니다.

npm run inspector

검사기는 브라우저에서 디버깅 도구에 액세스할 수 있는 URL을 제공합니다.

Available Tools

1 tool
generate_imageC

Generate an image from a prompt.

ParametersJSON Schema
NameRequiredDescriptionDefault
promptYesA prompt detailing what image to generate.
imageNameYesThe filename for the image excluding any extensions.

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions generation but doesn't describe side effects (e.g., file creation, rate limits, permissions needed, or output format). For a tool that likely creates files, this lack of detail is a significant gap.

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 extremely concise with a single sentence that directly states the tool's function. It is front-loaded and wastes no words, making it easy to parse quickly. Every word earns its place.

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 (image generation likely involves file creation and AI processing), no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, output handling, and usage context, leaving significant gaps for an AI agent to understand how to invoke it correctly.

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%, so the schema already documents both parameters ('prompt' and 'imageName') adequately. The description adds no additional meaning beyond what the schema provides, such as prompt formatting tips or filename conventions. Baseline 3 is appropriate when schema does the heavy lifting.

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?

The description clearly states the tool's purpose with a specific verb ('generate') and resource ('image'), and specifies the input mechanism ('from a prompt'). It doesn't need sibling differentiation since there are no sibling tools. However, it could be more specific about the type of image generation (e.g., AI model, format).

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 description provides no guidance on when to use this tool versus alternatives, prerequisites, or constraints. It simply states what the tool does without context about appropriate use cases or limitations. With no sibling tools, this is less critical but still a gap.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • Addedgenerate_image
Deploy Server
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

B3.1/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools, as there are no other tools to compare it to. The tool's purpose is singular and clear, eliminating any risk of misselection.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect; there are no other tool names to compare it against, so no inconsistencies can arise. The tool name follows a clear verb_noun pattern (generate_image).

Tool Count2/5

A single tool is too few for a server named 'Image Generator MCP Server', as it suggests a limited scope that may not cover related operations like image editing, listing, or deletion. This minimal set could hinder agent workflows that require more comprehensive image management.

Completeness2/5

The tool set is severely incomplete for an image generation domain; it only provides generation without any support for retrieval, modification, deletion, or other common image operations. This creates significant gaps that will likely cause agent failures in broader tasks.

Resources

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