A
licenseNot graded
qualityF
maintenanceA server that provides AI-powered image generation, modification, and processing capabilities through the Model Context Protocol, leveraging Google Gemini models and other image services.
18
MIT
Ideogram MCP Server
📦 Descripción general del proyecto
Una herramienta de TypeScript que le permite utilizar la API de Ideogram (v3.0) a través del servidor MCP
Multifunción que incluye generación de imágenes, referencia de estilo, aviso mágico, relación de aspecto, selección de modelo, etc.
Se puede utilizar inmediatamente con Claude Desktop y otros clientes MCP
Related MCP server: OpenAI MCP
⚡️ Inicio rápido
Si desea conectarse a Claude Desktop u otros clientes MCP a la velocidad del rayo,
¡Simplemente copie y pegue el fragmento JSON a continuación en su archivo de configuración! ✨
{
"mcpServers": {
"ideogram": {
"command": "npx",
"args": [
"@sunwood-ai-labs/ideagram-mcp-server"
],
"env": {
"IDEOGRAM_API_KEY": "your_api_key_here"
}
}
}
}Especificaciones de la herramienta MCP
generar_imagen
Lista de parámetros (última versión)
Parámetros | Tipo | explicación | Obligatorio/Opcional | observaciones |
inmediato | cadena | Indicación de generación de imágenes (se recomienda usar inglés) | Requerido | |
relación de aspecto | cadena | Relación de aspecto (por ejemplo, "1x1", "16x9", "4x3", etc.) | cualquier | 15 tipos |
resolución | cadena | Resolución (ver documentación oficial, 69 tipos en total) | cualquier | |
semilla | entero | Semilla de número aleatorio (para garantizar la reproducibilidad) | cualquier | 0 a 2147483647 |
aviso mágico | cadena | Indicación mágica ("AUTO" | "EN" | "APAGADO" |
velocidad de renderizado | cadena | Velocidad de renderizado para v3 ("TURBO" | "POR DEFECTO" | "CALIDAD" |
códigos de estilo | cadena[] | Secuencia de código de estilo de 8 caracteres | cualquier | |
tipo_de_estilo | cadena | Tipo de estilo ("AUTO" | "GENERAL" | "REALISTA" |
mensaje negativo | cadena | Exclusiones (se recomienda inglés) | cualquier | |
número de imágenes | número | Número de imágenes generadas (1 a 8) | cualquier | |
referencia de estilo | objeto | Referencia de estilo (Novedad en Ideograma 3.0) | cualquier | Detalles a continuación |
└ URL | cadena[] | Matriz de URL de imágenes de referencia (hasta 3) | cualquier | |
└ código de estilo | cadena | Código de estilo | cualquier | |
└ estilo aleatorio | booleano | Utilice un estilo aleatorio | cualquier | |
directorio_de_salida | cadena | Directorio de almacenamiento de imágenes (predeterminado: "docs") | cualquier | |
nombre_de_archivo_base | cadena | Base para el nombre del archivo guardado (predeterminado: "ideogram-image") | cualquier | Marca de tiempo y asignación de ID |
máscara borrosa | booleano | Desenfocar los bordes de la imagen (establecer como verdadero para la composición de máscara) | cualquier | Predeterminado: falso |
📝 Ejemplo de uso
const result = await use_mcp_tool({
server_name: "ideagram-mcp-server",
tool_name: "generate_image",
arguments: {
prompt: "A beautiful sunset over mountains",
aspect_ratio: "16x9",
rendering_speed: "QUALITY",
num_images: 2,
style_reference: {
urls: [
"https://example.com/ref1.jpg",
"https://example.com/ref2.jpg"
],
random_style: false
},
blur_mask: true
}
});🧑💻 Desarrollar, construir y probar
npm run build... Compilación de TypeScriptnpm run watch... modo de desarrollo (compilación automática)npm run lint... Revisión de códigonpm test... ejecutar pruebas
🗂️ Estructura del directorio
ideagram-mcp-server/
├── assets/
├── docs/
│ └── ideogram-image_2025-05-18T06-31-45-777Z.png
├── src/
│ ├── tools/
│ ├── types/
│ ├── utils/
│ ├── ideogram-client.ts
│ ├── index.ts
│ ├── server.ts
│ └── test.ts
├── .env.example
├── package.json
├── tsconfig.json
├── README.md
└── ...（省略）📝 Contribuciones
Bifurcar este repositorio
Crea una nueva rama (
git checkout -b feature/awesome)Confirmar cambios (los mensajes de confirmación deben estar en japonés y se recomiendan usar emojis)
Creación de solicitudes push y pull
🚀 Implementar y lanzar
Publicación automática de npm con GitHub Actions
Actualización de versión → Implementación automática mediante el envío de etiquetas
npm version patch|minor|major
git push --follow-tagsPara obtener más detalles, consulte docs/npm-deploy.md .
📄 Licencia
Instituto Tecnológico de Massachusetts (MIT)
Available Tools
1 toolgenerate_imageC
Generate an image using Ideogram AI
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The prompt to use for generating the image (must be in English) | |
| aspect_ratio | No | The aspect ratio for the generated image (see official docs for all 15 values) | |
| resolution | No | The resolution for the generated image (see official docs for all 69 values) | |
| seed | No | Random seed. Set for reproducible generation. | |
| magic_prompt | No | Whether to use magic prompt | |
| rendering_speed | No | Rendering speed for v3 (TURBO/DEFAULT/QUALITY) | |
| style_codes | No | Array of 8-char style codes | |
| style_type | No | The style type for generation | |
| style_reference_images | No | A set of images to use as style references (max 10MB, JPEG/PNG/WebP) | |
| negative_prompt | No | Description of what to exclude from the image (must be in English) | |
| num_images | No | Number of images to generate (1-8) | |
| style_reference | No | Style reference options for Ideogram 3.0 | |
| output_dir | No | Directory to save generated images (default: 'docs'). | |
| base_filename | No | Base filename for saved images (default: 'ideogram-image'). Timestamp and image ID will be appended automatically. | |
| blur_mask | No | Apply a blurred mask to the image edges (using a fixed mask image). If true, the output image will have blurred/feathered edges. (default: false) |
TDQS
C2.7/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states the basic action without mentioning rate limits, authentication needs, output format, error conditions, or cost implications. For a complex image generation tool with 15 parameters, this leaves significant behavioral gaps.
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 a single, efficient sentence that states the core purpose without unnecessary elaboration. It's appropriately sized for a tool name that clearly indicates its function, and there's no wasted verbiage or structural issues.
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 (15 parameters, no output schema, no annotations), the description is inadequate. It doesn't explain what the tool returns, error handling, performance characteristics, or typical use patterns. For an image generation tool with many configuration options, more context is needed to help the agent use it effectively.
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 all parameters thoroughly. The description adds no parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate an image using Ideogram AI' states the basic action (generate) and resource (image) but lacks specificity. It doesn't mention what kind of images, quality levels, or typical use cases. Without sibling tools, differentiation isn't needed, but the purpose remains vague beyond the basic verb-noun pairing.
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 is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, ideal scenarios, or limitations. Without sibling tools, there's no need for differentiation, but the absence of any usage context leaves the agent with no guidance on appropriate application.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
C2.9/5.0
Disambiguation5/5
With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'generate_image' has a clearly distinct and unambiguous purpose.
Naming Consistency5/5
A single tool inherently has perfect naming consistency, as there are no other tools to compare it against. The name 'generate_image' follows a clear verb_noun pattern.
Tool Count2/5
One tool is too few for a server named 'Ideogram MCP Server', which suggests a broader scope for image generation or AI tasks. A single tool feels thin and limited for such a domain.
Completeness2/5
The tool surface is severely incomplete for an image generation server. It only offers generation with no options for editing, listing, deleting, or managing images, creating significant gaps in functionality.
Maintenance
ActivityInactive
ResponsivenessNo issues
Resources
Unclaimed servers have limited discoverability.
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