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Image Generation MCP Server

by mikeyny
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

画像生成MCPサーバー

Replicate のblack-forest-labs/flux-schnellモデルを使用して画像を生成するためのMCP (Model Context Protocol)サーバー実装。

理想的には、Cursor の MCP 機能と一緒に使用しますが、どの MCP クライアントでも使用できます。

特徴

  • テキストプロンプトから画像を生成する

  • 設定可能な画像パラメータ（解像度、アスペクト比、品質）

  • 生成された画像を指定されたディレクトリに保存する

  • MCPプロトコルに完全準拠

  • エラー処理と検証

Related MCP server: replicate-flux-mcp

前提条件

  • Node.js 16以上

  • APIトークンを複製する

  • MCP 向け TypeScript SDK

設定

  1. リポジトリをクローンする

  2. 依存関係をインストールします:

    npm install

  3. apiToken定数を更新して、 src/imageService.tsのコードに Replicate API トークンを直接追加します。

    // No environment variables are used since they can't be easily set in cursor
const apiToken = "your-replicate-api-token-here";

    注: Claude で使用する場合は、ルート ディレクトリに.envファイルを作成し、そこに API トークンを設定できます。

    REPLICATE_API_TOKEN=your-replicate-api-token-here

    次にプロジェクトをビルドします。

    npm run build

使用法

カーソルで使用するには:

  1. 設定に移動

  2. 機能を選択

  3. 「MCPサーバー」までスクロールします。

  4. 「新しいMCPサーバーを追加」をクリックします

  5. タイプを「コマンド」に設定する

  6. コマンドを次のように設定します: node ./path/to/dist/server.js

APIパラメータ

パラメータ

タイプ

必須

デフォルト

説明

prompt

弦

はい

-

画像生成のためのテキストプロンプト

output_dir

弦

はい

-

生成された画像を保存するサーバーディレクトリパス

go_fast

ブール値

いいえ

間違い

高速生成モードを有効にする

megapixels

弦

いいえ

「1」

解像度の品質（「1」、「2」、「4」）

num_outputs

番号

いいえ

1

生成する画像の数（1～4）

aspect_ratio

弦

いいえ

「1:1」

アスペクト比（「1:1」、「4:3」、「16:9」）

output_format

弦

いいえ

「ウェブ」

画像形式（「webp」、「png」、「jpeg」）

output_quality

番号

いいえ

80

圧縮品質（1～100）

num_inference_steps

番号

いいえ

4

ノイズ除去ステップ数（4～20）

リクエスト例

{
  "prompt": "black forest gateau cake spelling out 'FLUX SCHNELL'",
  "output_dir": "/var/output/images",
  "filename": "black_forest_cake",
  "output_format": "webp"
  "go_fast": true,
  "megapixels": "1",
  "num_outputs": 2,
  "aspect_ratio": "1:1"
}

回答例

{
  "image_paths": [
    "/var/output/images/output_0.webp",
    "/var/output/images/output_1.webp"
  ],
  "metadata": {
    "model": "black-forest-labs/flux-schnell",
    "inference_time_ms": 2847
  }
}

エラー処理

サーバーは次のエラー タイプを処理します。

  • 検証エラー（無効なパラメータ）

  • API エラー (API の問題を複製する)

  • サーバーエラー（ファイルシステム、権限）

  • 不明なエラー（予期しない問題）

各エラー応答には次の内容が含まれます。

  • エラーコード

  • 人間が読めるメッセージ

  • 詳細なエラー情報

ライセンス

ISC

Available Tools

1 tool
generate-imageC

Generate an image based on a prompt

ParametersJSON Schema
NameRequiredDescriptionDefault
promptYes
output_dirYesFull absolute path to output directory. For Windows, use double backslashes like 'C:\\Users\\name\\path'. For Unix/Mac use '/path/to/dir'. Always use the proper path otherwise you will get an error.
filenameNoBase filename to save the image(s) with
go_fastNo
megapixelsNo
num_outputsNo
aspect_ratioNo
output_formatNo
output_qualityNo
num_inference_stepsNo

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the core action (generating images from prompts) but lacks critical behavioral details like whether this is a local or cloud operation, rate limits, authentication requirements, error handling, or what happens when files are saved. The description doesn't contradict annotations since none exist.

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 at just 5 words, front-loaded with the core functionality. Every word earns its place, and there's no wasted text or redundancy.

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?

For a complex tool with 10 parameters, no annotations, no output schema, and low schema description coverage, the description is severely inadequate. It doesn't explain what the tool returns, how outputs are structured, error conditions, or provide enough context for an agent to use it effectively beyond the most basic invocation.

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

Parameters2/5

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

With only 20% schema description coverage, the description must compensate but fails to do so. It mentions 'based on a prompt' which hints at one parameter but doesn't explain the other 9 parameters or their relationships. The description adds minimal value beyond what's already in the schema.

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 it's based on a prompt. It's unambiguous about what the tool does, though it doesn't distinguish from siblings since there are none.

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, nor any context about prerequisites or limitations. It simply states what the tool does without indicating appropriate use cases.

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 update
    • First observedgenerate-image
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'generate-image' has a clear and distinct purpose for image generation based on prompts.

Naming Consistency5/5

The single tool name 'generate-image' follows a clear verb_noun pattern. Since there is only one tool, consistency is inherently perfect with no deviations or mixed conventions to evaluate.

Tool Count2/5

A single tool is too few for a server named 'Image Generation MCP Server', which suggests a broader scope. While it covers basic generation, typical image generation domains might include variations, edits, or management tools, making this feel thin and incomplete.

Completeness2/5

The tool surface is severely incomplete for image generation. It only provides generation, with no tools for editing, resizing, filtering, or managing images, leaving obvious gaps that will limit agent capabilities in this domain.

Maintenance

ActivityInactive
ResponsivenessNo issues

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