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
📦 Projektübersicht
Ein TypeScript-Tool, mit dem Sie die Ideogram-API (v3.0) über den MCP-Server verwenden können
Multifunktional, einschließlich Bildgenerierung, Stilreferenz, magische Eingabeaufforderung, Seitenverhältnis, Modellauswahl usw.
Kann sofort mit Claude Desktop und anderen MCP-Clients verwendet werden
Related MCP server: OpenAI MCP
⚡️ Schnellstart
Wenn Sie sich blitzschnell mit Claude Desktop oder anderen MCP-Clients verbinden möchten,
Kopieren Sie einfach den folgenden JSON-Ausschnitt und fügen Sie ihn in Ihre Konfigurationsdatei ein! ✨
{
"mcpServers": {
"ideogram": {
"command": "npx",
"args": [
"@sunwood-ai-labs/ideagram-mcp-server"
],
"env": {
"IDEOGRAM_API_KEY": "your_api_key_here"
}
}
}
}🛠️ MCP-Tool-Spezifikationen
Bild generieren
Parameterliste (neueste Version)
Parameter | Typ | Erläuterung | Erforderlich/Optional | Bemerkungen |
prompt | Schnur | Eingabeaufforderung zur Bildgenerierung (Englisch empfohlen) | Erforderlich | |
Seitenverhältnis | Schnur | Seitenverhältnis (z. B. „1x1“, „16x9“, „4x3“ usw.) | beliebig | 15 Typen |
Auflösung | Schnur | Auflösung (siehe offizielle Dokumentation, insgesamt 69 Typen) | beliebig | |
Samen | ganze Zahl | Zufallszahlen-Startwert (um die Reproduzierbarkeit sicherzustellen) | beliebig | 0 bis 2147483647 |
magische Eingabeaufforderung | Schnur | Magische Eingabeaufforderung ("AUTO" | "AN" | "AUS" |
Rendering-Geschwindigkeit | Schnur | Rendering-Geschwindigkeit für v3 („TURBO“ | "STANDARD" | "QUALITÄT" |
Stilcodes | Zeichenfolge[] | 8-stellige Codesequenz | beliebig | |
Stiltyp | Schnur | Stiltyp ("AUTO" | "ALLGEMEIN" | "REALISTISCH" |
negative_prompt | Schnur | Ausschlüsse (Englisch empfohlen) | beliebig | |
Anzahl Bilder | Nummer | Anzahl der generierten Bilder (1 bis 8) | beliebig | |
Stilreferenz | Objekt | Stilreferenz (Neu in Ideogram 3.0) | beliebig | Details unten |
└ URLs | Zeichenfolge[] | Referenzbild-URL-Array (bis zu 3) | beliebig | |
└ Stilcode | Schnur | Stilcode | beliebig | |
└ zufälliger Stil | Boolescher Wert | Zufälligen Stil verwenden | beliebig | |
Ausgabeverzeichnis | Schnur | Bildspeicherverzeichnis (Standard: „docs“) | beliebig | |
Basisdateiname | Schnur | Basis für gespeicherten Dateinamen (Standard: „Ideogramm-Bild“) | beliebig | Zeitstempel und ID-Zuweisung |
Unschärfemaske | Boolescher Wert | Die Ränder des Bildes verwischen (für die Maskenzusammenstellung auf „true“ setzen) | beliebig | Standard: false |
📝 Anwendungsbeispiel
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
}
});🧑💻 Entwickeln, bauen und testen
npm run build... TypeScript-Buildnpm run watch... Entwicklungsmodus (automatischer Build)npm run lint... Code-Lintingnpm test... Tests ausführen
🗂️ Verzeichnisstruktur
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）📝 Beiträge
Forken Sie dieses Repository
Erstellen Sie einen neuen Zweig (
git checkout -b feature/awesome)Änderungen festschreiben (Commit-Nachrichten sollten auf Japanisch sein und Emojis werden empfohlen!)
Push- und Pull-Anforderungserstellung
🚀 Bereitstellen und Freigeben
Automatische NPM-Veröffentlichung mit GitHub Actions
Versionsupdate → Automatisches Deployment durch Pushen von Tags
npm version patch|minor|major
git push --follow-tagsEinzelheiten finden Sie unter docs/npm-deploy.md !
📄 Lizenz
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.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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