mcp-vision
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ARK_API_KEY | Yes | 视觉模型凭据 | |
| ARK_BASE_URL | Yes | OpenAI 兼容接入点（/chat/completions） | |
| VISION_MODEL | Yes | 视觉模型 id | |
| VISION_TIMEOUT | No | 请求超时秒数（默认 60） | 60 |
| VISION_MAX_TOKENS | No | 单次识别最大输出 token（默认 2048） | 2048 |
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 |
|---|---|
| recognize_imageA | 识别图片内容并返回文字描述。 适用于截图分析、UI 审查、图片内容理解、图表解读等场景。 Args: image: 图片来源，支持三种形式： 1. 本地文件绝对/相对路径（如 /tmp/a.png、./pic.jpg） 2. http(s) 网络图片 URL 3. base64 编码字符串（裸串即可，无需 data: 前缀） prompt: 想让模型关注的重点或要回答的问题。 默认为详细描述图片全部内容。 Returns: 视觉模型给出的图片文字描述。 Raises: FileNotFoundError: 本地图片路径不存在。 RuntimeError: 未配置 API key 或视觉模型调用失败。 |
| ocr_imageA | 提取图片中的所有文字内容（OCR），保持原始排版。 与 recognize_image 的区别：本工具只提取文字，不描述图像本身， 适合截图取字、票据/单据录入、文档数字化等场景。 Args: image: 图片来源，支持本地路径 / http(s) URL / base64 字符串。 Returns: 图片中识别到的纯文本内容。 |
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 2 tools
The two tools have clearly distinct purposes: ocr_image extracts text only, while recognize_image describes image content. The descriptions explicitly contrast them, leaving no ambiguity.
Both tools follow a consistent verb_noun snake_case pattern: 'ocr_image' and 'recognize_image'. This creates a predictable and clear naming convention.
With only 2 tools, the server feels minimal for a vision-focused service. While the tools cover basic OCR and general image recognition, the count is on the low end for the domain.
The server provides core text extraction and image description, but lacks other common vision operations like object detection, image generation, or format conversion. The surface is adequate for narrow use cases but not comprehensive.