deepseek-vision-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ZHIPU_API_KEY | Yes | Your Zhipu API key for accessing GLM-4.6V-Flash |
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 |
|---|---|
| vision_analyze_imageA | 分析一张图片并回答问题。source 为本地图片路径（自动转 base64）或公网 URL； question 为对图片的提问；thinking=True 开启深度思考模式（更慢但更深入）。 返回 JSON：{ok, content, thinking, usage} 或 {ok:false, error:{code,message}}。 |
| vision_analyze_videoA | 分析一段视频并回答问题。source 仅支持公网可访问的视频 URL（如 https://...）； 本地视频请先上传到可访问地址。question 为对视频的提问；thinking=True 开启深度思考。 返回 JSON：{ok, content, thinking, usage} 或 {ok:false, error:{code,message}}。 |
| vision_analyze_fileA | 分析一个文档文件（PDF / 文本等）并回答问题。source 仅支持公网可访问的文件 URL； 本地文件请先上传到可访问地址。question 为对文档的提问；thinking=True 开启深度思考。 返回 JSON：{ok, content, thinking, usage} 或 {ok:false, error:{code,message}}。 |
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 3 tools
Each tool targets a distinct media type: image, video, and document file. The purpose of each is clearly separated by the input format, leaving no ambiguity about which tool to use for a given source.
All tools follow the consistent pattern `vision_analyze_<type>`, making it easy to predict the tool name for new media types. The verb `analyze` and prefix `vision_` are used uniformly.
Three tools cover the core capabilities of the server (image, video, and document analysis) without unnecessary bloat. This is a well-scoped set for a vision-focused server.
The set covers the primary media types (image, video, document), but local video and file inputs require public URLs, which could be a usability gap. Missing audio analysis is a minor omission but not core to vision.