glm-vision-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| ZHIPU_API_KEY | Yes | Your API key for Zhipu AI platform |
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
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_imageA | 分析图片内容。支持传入图片URL或本地文件路径，可附带自定义分析指令。 |
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
With only one tool, there is no possibility of confusion or overlap. The tool's purpose is clearly defined as image analysis, so an agent can unambiguously select it for any image-related task.
The single tool 'analyze_image' follows a clean verb_noun pattern, which is consistent with common API naming conventions. While there are no other tools to compare, the name is descriptive and predictable.
The server has only one tool, which is slightly below the typical 3-15 range, but it is tailored specifically for vision-based image analysis. The single tool is reasonably scoped for this narrow purpose, and adding more tools could dilute its focus.
The tool covers the core and likely only operation needed for image analysis: accepting an image URL or local path and allowing custom instructions. There are no obvious gaps or dead ends for this domain, as the tool provides a complete workflow for its intended use.