visual-understand-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VISION_MODEL | Yes | 视觉模型名称 | |
| VISION_API_KEY | Yes | 视觉模型密钥 | |
| VISION_TIMEOUT | No | 请求超时（秒） | 120 |
| VISION_API_BASE | Yes | 视觉模型 API 地址 | |
| VISION_MAX_TOKENS | No | 最大输出长度 | 12000 |
| VISION_TEMPERATURE | No | 输出随机性 | 0.1 |
| VISION_SYSTEM_PROMPT | No | 视觉模型系统提示词 |
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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| understand_imageA | 调用视觉模型理解图片，将识别结果以文本返回。 当用户要求识别、分析、OCR、描述、比较图片或截图时，必须调用此工具。 这是唯一可以"看到"图片的工具，不要用 Read/cat 等文本工具打开图片文件。 Args: prompt: 图片理解任务描述，如"提取图中文字"、"分析截图中的报错信息"。 image_path: 单张本地图片路径。 image_url: 单张网络图片 URL 或 data:image base64 格式。 image_paths: 多张本地图片路径列表。 image_urls: 多张网络图片 URL 列表。 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| get_vision_config | 查看当前视觉模型配置（API Key 脱敏）。 |
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of confusion between tools.
The single tool 'understand_image' follows a clear verb_noun pattern, which is consistent and intuitive.
With only one tool, the server feels thin for typical use cases; a broader domain like visual understanding might benefit from more specialized tools.
The tool's comprehensive description covers recognition, analysis, OCR, description, and comparison of both single and multiple images, leaving no obvious gaps.