mcp-vision-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VISION_MODEL | No | Model name. | |
| VISION_API_KEY | No | API key for the vision provider. | |
| VISION_BASE_URL | No | OpenAI-compatible endpoint URL. | |
| VISION_PROVIDER | No | Provider preset name (zhipu, bailian, deepseek, openai, etc.) | zhipu |
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 |
|---|---|
| list_providersA | List all supported provider presets as a JSON array. |
| analyze_imageB | Analyze or understand an image. Use this tool when an MCP client needs image understanding, screenshot analysis, OCR-like text recognition, visual Q&A, or UI restoration. |
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 entirely distinct purposes: analyze_image for image understanding and list_providers for listing provider presets. No overlap or ambiguity.
Both tools follow a consistent verb_noun pattern (analyze_image, list_providers), making naming predictable and clear.
Only two tools for a vision server feels slightly thin. While the count is not extreme, it borders on insufficient for typical vision tasks.
The server covers only basic image analysis and a provider listing, missing common vision operations like generation, manipulation, or filtering. The tool surface is significantly incomplete.