agnes-image-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| AGNES_MODEL | No | Default model name. If omitted, the server uses agnes-image-2.5-flash. | |
| AGNES_API_KEY | Yes | Agnes API credential. Keep it in the environment or a secret manager; never put it in source code or an MCP JSON file committed to version control. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageA | 使用 Agnes 模型生成一张图片。支持文生图或参考图输入，可返回图片 URL 或 base64；会调用远程 Agnes API。 |
| generate_imagesA | 按顺序批量调用 Agnes 生成图片，默认遇错停止；可选择继续处理并返回每项成功、失败和跳过统计。 |
| download_imageA | 从经过安全校验的 HTTPS 公网地址下载图片到当前工作目录下的相对路径；拒绝内网地址、路径越界、链接和覆盖已有文件。 |
| validate_imageA | 读取当前工作目录下的相对路径，校验本地文件大小及 PNG、JPEG、GIF、WebP 格式，不访问网络也不修改文件。 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: single generation, batch generation, downloading, and validating images. The singular/plural naming clearly separates generate_image from generate_images, and download/validate do not overlap with generation.
All tool names follow the same verb_noun snake_case pattern: generate_image, generate_images, download_image, validate_image. The pluralization is intentional and consistent with the batch behavior.
Four tools are well-scoped for an image generation server covering creation, batch creation, download, and validation. The count is small enough to avoid overload while providing a complete practical workflow.
The server covers the core image generation workflow: single generation, batch generation, downloading results, and validating local files. Minor gaps exist, such as no explicit image editing or metadata retrieval, but these are not essential to its stated purpose.