mcp-vision-analyze
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VISION_MODEL | No | Gemini model to use | google/gemini-2.5-flash-lite |
| OPENROUTER_API_KEY | Yes | Your OpenRouter API key |
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 | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| vision_analyzeA | Analyze an image using AI vision (Gemini via OpenRouter). Accepts local file paths or HTTP(S) URLs. Returns a detailed text analysis of the image content. |
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
The server has exactly one tool, so there is no possibility of confusing it with others. Its purpose is clearly stated and distinct.
The single tool follows a clean verb_noun pattern (vision_analyze), which is consistent and self-explanatory.
With only one tool, the server is extremely minimal and feels thin for broader workflows, though it is not trivial and adequately serves a focused purpose.
For a server dedicated solely to image analysis, the single tool fully covers the intended capability. There are no obvious missing operations within this narrow domain.