image-understand-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VISION_MODEL | No | 模型名称 | |
| VISION_API_KEY | No | API Key | |
| VISION_BASE_URL | No | 视觉模型 API 的 base URL（不含 /chat/completions） | |
| VISION_PROVIDERS | No | JSON 数组，配置多个 provider（见 README 示例） | |
| VISION_TIMEOUT_MS | No | 单次请求超时时间（毫秒），默认 60000 | 60000 |
| VISION_DEFAULT_PROVIDER | No | 多 provider 时的默认 provider 名称 |
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 |
|---|---|
| understand_imageA | 分析一张图片并返回详细的文字描述。用于让不具备视觉能力的纯文本模型间接'看懂'图片：传入本地文件路径、图片 URL 或 base64 编码数据，本工具会调用配置好的视觉模型完成识别，并返回自然语言描述文本。适合需要理解截图、照片、图表、文档扫描件等内容的场景。 |
| list_vision_providersA | 列出当前 MCP 服务配置的所有视觉模型 provider 及其名称、模型标识，以及默认使用哪一个。 |
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 2 tools
The two tools have clearly distinct purposes: understand_image performs image analysis, while list_vision_providers only lists configured providers. There is no overlap in function or input, so an agent can easily select the correct tool.
Both names use snake_case and follow a verb_noun pattern: understand_image and list_vision_providers. The convention is consistent and predictable across the entire set.
With only 2 tools, the set is borderline thin; one is a core operation and the other is auxiliary. While it matches the narrow purpose, it falls below the typical 3–15 range for a well-scoped server.
The core operation of understanding images and a helper to list providers are present, covering the main workflow. A minor gap exists: understand_image uses the configured default model with no parameter to select a specific provider per call, despite list_vision_providers exposing options.