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Image Generator MCP Server

by sammyl720
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

画像生成器MCPサーバー

画像プロンプトに基づいて画像を生成するmcpサーバー

これは、 OPENAIのdall-e-3画像生成モデルを使用して画像生成を実装した TypeScript ベースの MCP サーバーです。

特徴

ツール

  • generate_image - 指定されたプロンプトの画像を生成する

    • prompt必須パラメータとして受け取ります

    • 生成された画像をデスクトップのgenerated-imagesディレクトリに保存するには、 imageName必須パラメータとして受け取ります。

Related MCP server: Image Generator MCP Server

発達

依存関係をインストールします:

npm install

サーバーを構築します。

npm run build

自動リビルドを使用した開発の場合:

npm run watch

インストール

Claude Desktop で使用するには、サーバー設定を追加します。

MacOS の場合: ~/Library/Application Support/Claude/claude_desktop_config.json Windows の場合: %APPDATA%/Claude/claude_desktop_config.json

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

<your-openai-api-key>実際のOPENAI Api キーに置き換えてください。

デバッグ

MCPサーバーはstdio経由で通信するため、デバッグが困難になる場合があります。パッケージスクリプトとして提供されているMCP Inspectorの使用をお勧めします。

npm run inspector

インスペクターは、ブラウザでデバッグ ツールにアクセスするための URL を提供します。

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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