image-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VISION_MODEL | Yes | The vision model to use (e.g., qwen-vl-plus). | |
| DASHSCOPE_API_KEY | Yes | Your DashScope API key. | |
| DASHSCOPE_BASE_URL | No | The base URL for the DashScope API. Can be omitted. | https://dashscope.aliyuncs.com/compatible-mode/v1 |
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 |
|---|---|
| recognize_imageA | 识别本地或远程图片内容，默认使用 XML 形式输出，帮助 AI 理解图片内容。 |
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 1 tool
Only one tool exists, so there is no possibility of confusion between tools. The single recognize_image tool has a clear and distinct purpose.
The tool name recognize_image follows a clear verb_noun pattern, which is descriptive and predictable. With only one tool, the naming convention is inherently consistent.
Having a single tool feels thin for an image-related server. While the tool covers the core recognition function, the server lacks any additional utilities, making it borderline in scope.
The server's stated purpose is to help AI understand image content, and recognize_image fulfills this completely. There are no obvious missing operations within this narrow domain.