agent-vision-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VISION_API_KEY | Yes | API key for the OpenAI-compatible endpoint | |
| VISION_BASE_URL | No | OpenAI-compatible base URL | https://api.openai.com/v1 |
| VISION_CACHE_DIR | No | Cache directory (when enabled) | <tmp>/agent-vision-cache |
| VISION_MAX_TOKENS | No | Output token budget | 16384 |
| VISION_MODEL_NAME | No | The vision model, e.g. Qwen3.6-35B-A3B | gpt-4o |
| VISION_TIMEOUT_MS | No | Per-request client timeout | 300000 |
| VISION_MAX_RETRIES | No | Retries for empty / 5xx / 429 / network errors | 3 |
| VISION_CACHE_ENABLED | No | Optional disk response cache | false |
| VISION_MAX_IMAGE_SIZE | No | Max image bytes (20 MB) | 20971520 |
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": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_imageA | Analyze an image with a vision AI model, giving a non-vision main model the ability to "see" image content. Call this when the user sends an image, or when you need to understand an image (describe it, OCR text, identify UI elements, read charts, etc.). The image can be provided as a base64 data URL, an HTTP(S) link, or a local file path. |
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
There is only one tool, so there is no possibility of ambiguity or misselection. The tool's purpose is clearly distinct and singular.
With a single tool named 'analyze_image', the naming follows a clear and consistent verb_noun pattern. There are no other tools to introduce inconsistency.
The server has only one tool, which is below the typical 3-15 range, but it is a narrow-purpose server focused on image analysis. The single tool is well-scoped and earns its place, making the count slightly under but reasonable.
The single tool covers a wide range of image analysis needs—description, OCR, UI element detection, chart reading, etc. There are no obvious gaps for the stated purpose of giving a non-vision model the ability to see.