Ideogram MCP Server

📦项目概述
一个 TypeScript 工具,允许您通过 MCP 服务器使用 Ideogram API (v3.0)
多功能包括图像生成、样式参考、魔法提示、长宽比、模型选择等。
可立即与 Claude Desktop 和其他 MCP 客户端一起使用
Related MCP server: OpenAI MCP
⚡️ 快速入门
如果你想以闪电般的速度连接到 Claude Desktop 或其他 MCP 客户端,
只需将下面的 JSON 代码片段复制并粘贴到您的配置文件中! ✨
{
"mcpServers": {
"ideogram": {
"command": "npx",
"args": [
"@sunwood-ai-labs/ideagram-mcp-server"
],
"env": {
"IDEOGRAM_API_KEY": "your_api_key_here"
}
}
}
}🛠️ MCP 工具规格
生成图像
参数列表(最新版本)
参数 | 类型 | 解释 | 必需/可选 | 评论 |
迅速的 | 细绳 | 图像生成提示(建议使用英文) | 必需的 | |
纵横比 | 细绳 | 长宽比(例如“1x1”、“16x9”、“4x3”等) | 任何 | 15种 |
解决 | 细绳 | 分辨率(参见官方文档,共69种) | 任何 | |
种子 | 整数 | 随机数种子(确保可重复性) | 任何 | 0 到 2147483647 |
magic_prompt | 细绳 | 魔术提示(“AUTO” | “在” | “离开” |
渲染速度 | 细绳 | v3 的渲染速度(“TURBO” | “默认” | “质量” |
样式代码 | 细绳[] | 8 个字符的样式代码序列 | 任何 | |
样式类型 | 细绳 | 样式类型(“AUTO” | “一般的” | “实际的” |
负面提示 | 细绳 | 除外责任(建议使用英语) | 任何 | |
图像数量 | 数字 | 生成的图像数量(1 至 8) | 任何 | |
样式参考 | 目的 | 样式参考(表意文字 3.0 中的新功能) | 任何 | 详情如下 |
└ 网址 | 细绳[] | 参考图像 URL 数组(最多 3 个) | 任何 | |
└ 样式代码 | 细绳 | 样式代码 | 任何 | |
└ 随机风格 | 布尔值 | 使用随机样式 | 任何 | |
输出目录 | 细绳 | 图片存储目录(默认:“docs”) | 任何 | |
基本文件名 | 细绳 | 保存文件名的基础(默认值:“ideogram-image”) | 任何 | 时间戳和ID分配 |
模糊蒙版 | 布尔值 | 模糊图像边缘(设置为 true 以进行蒙版合成) | 任何 | 默认值:false |
📝 使用示例
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
}
});🧑💻 开发、构建和测试
npm run build... TypeScript 构建npm run watch... 开发模式(自动构建)npm run lint... 代码检查npm test...运行测试
🗂️ 目录结构
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)📝 贡献
Fork此存储库
创建新分支(
git checkout -b feature/awesome)提交更改(提交消息应使用日语,并建议使用表情符号!)
推送和拉取请求创建
🚀 部署和发布
使用 GitHub Actions 自动进行 npm 发布
版本更新→推送标签自动部署
npm version patch|minor|major
git push --follow-tags有关详细信息,请参阅docs/npm-deploy.md !
📄 许可证
麻省理工学院
Available Tools
1 toolgenerate_imageC
Generate an image using Ideogram AI
| 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
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.
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.
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.
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.
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.
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
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.
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.
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.
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
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