即梦AI图片生成 MCP
Utilizes TypeScript for type-safe implementation, providing a robust MCP service for generating AI images through the Volcengine Jimeng AI image generation API.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@即梦AI图片生成 MCPgenerate a birthday card with 'Happy Birthday' text, balloons and confetti, blue background, 4:3 ratio"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
即梦AI图片生成 MCP 服务
基于火山引擎即梦AI的图片生成MCP(Model Context Protocol)服务。
功能特性
使用火山引擎即梦AI API生成高质量图片
支持多种图片比例:4:3、3:4、16:9、9:16
标准化的MCP接口,兼容各种MCP客户端
环境变量配置,安全便捷
Related MCP server: Jimeng AI Image Generator
安装依赖
cd jimengpic-mcp
npm install编译项目
npm run build环境变量配置
设置以下环境变量:
export JIMENG_ACCESS_KEY="你的火山引擎AccessKey"
export JIMENG_SECRET_KEY="你的火山引擎SecretKey"获取API密钥
访问 火山引擎控制台
登录后进入"即梦AI"产品页面,开通服务(可选择免费试用)
在"访问控制"页面创建访问密钥,获取Access Key和Secret Key
确保账号已开通即梦AI图像生成相关权限和策略
注意: 根据官方文档,请确保使用正确的req_key参数值 jimeng_high_aes_general_v21_L
使用方法
直接运行
node build/index.js作为MCP服务器
在MCP客户端(如Claude Desktop、Cursor等)中配置此服务:
{
"mcpServers": {
"jimengpic": {
"command": "node",
"args": ["/path/to/jimengpic-mcp/build/index.js"],
"env": {
"JIMENG_ACCESS_KEY": "你的AccessKey",
"JIMENG_SECRET_KEY": "你的SecretKey"
}
}
}
}API接口
generate-image
当用户需要生成图片时使用的工具。
参数:
text(string): 用户需要在图片上显示的文字illustration(string): 根据用户要显示的文字,提取3-5个可以作为图片配饰的插画元素关键词color(string): 图片的背景主色调ratio(enum): 图片比例,支持以下选项:"4:3": 512×384"3:4": 384×512"16:9": 512×288"9:16": 288×512
提示词生成规则: 工具会自动将输入参数组合成以下格式的提示词:
字体设计:"{text}",黑色字体,斜体,带阴影。干净的背景,白色到{color}渐变。点缀浅灰色、半透明{illustration}等元素插图做配饰插画。返回:
成功时返回图片URL和详细信息
失败时返回错误信息
使用示例
// 在MCP客户端中调用
const result = await mcp.callTool("generate-image", {
text: "新年快乐",
illustration: "烟花, 灯笼, 祥云, 星星, 礼花",
color: "红色",
ratio: "4:3"
});项目结构
jimengpic-mcp/
├── src/
│ └── index.ts # 主服务文件
├── build/ # 编译输出目录
├── package.json # 项目配置
├── tsconfig.json # TypeScript配置
└── README.md # 项目说明注意事项
确保网络连接正常,能够访问火山引擎API
API调用需要消耗积分,请注意使用量
生成的图片URL有时效性,建议及时下载保存
请遵守火山引擎的使用条款和即梦AI的内容政策
故障排除
常见错误
环境变量未设置:确保设置了正确的ACCESS_KEY和SECRET_KEY
网络连接问题:检查网络连接和防火墙设置
API配额不足:检查火山引擎账户余额和API调用次数
提示词不合规:确保提示词符合内容安全规范
调试方法
运行时添加调试信息:
DEBUG=* node build/index.js许可证
ISC License
Available Tools
1 toolgenerate-imageC
当用户需要生成图片时使用的工具
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | 用户需要在图片上显示的文字 | |
| illustration | Yes | 根据用户要显示的文字,提取3-5个可以作为图片配饰的插画元素关键词 | |
| color | Yes | 图片的背景主色调 | |
| ratio | Yes | 图片比例。支持: 4:3 (512*384), 3:4 (384*512), 16:9 (512*288), 9:16 (288*512) |
TDQS
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 only states the tool is used for image generation, without details on output format, quality, limitations (e.g., rate limits, costs), or error handling. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
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, concise sentence in Chinese ('当用户需要生成图片时使用的工具'), which is efficient and front-loaded. However, it could be more structured by including key details upfront, but given its brevity and lack of redundancy, it earns a high score for conciseness.
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 (4 required parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain what the generated image looks like, how parameters interact, or any behavioral traits. Without annotations or output schema, the description should provide more context to compensate, but it falls short.
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?
The input schema has 100% description coverage, with clear parameter details (e.g., 'text' for displayed text, 'illustration' for accessory elements, 'color' for background, 'ratio' with enum values). The description adds no parameter semantics beyond what the schema provides, so it meets the baseline of 3 for high schema coverage without compensating value.
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 states the tool's purpose as '当用户需要生成图片时使用的工具' (used when users need to generate images), which is clear but vague. It specifies the general function (generate images) but lacks specificity about what kind of images or how it differs from other image generation tools (though no siblings exist). It's not tautological but doesn't provide detailed verb+resource context beyond the basic action.
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?
The description provides minimal guidance: it only states when to use the tool ('当用户需要生成图片时' - when users need to generate images), with no context on when not to use it, prerequisites, or alternatives. Since there are no sibling tools, this is less critical, but it still lacks depth in usage scenarios or constraints.
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 tool update
- First observed
generate-image
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined as generating images when needed by the user.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'generate-image' follows a clear verb_noun pattern and is descriptive of its function.
A single tool is too few for a server named '即梦AI图片生成 MCP' (Dream AI Image Generation MCP), which suggests a domain focused on image generation. This likely lacks essential operations like listing generated images, deleting images, or configuring generation parameters, making it feel thin and incomplete.
The server is severely incomplete for an image generation domain. It only provides a generate-image tool, missing obvious operations such as retrieving generated images, managing generation history, setting styles or parameters, and handling errors or status checks. This will cause significant agent failures in practical workflows.
Maintenance
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