Explain Image MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_MODEL | No | Default model id; override per call with the model argument | gemini-2.5-flash |
| GEMINI_API_KEY | Yes | Google AI Studio API key | |
| GEMINI_BASE_URL | No | OpenAI-compatible base URL (swap to add another provider later) | https://generativelanguage.googleapis.com/v1beta/openai |
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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| describe_imageA | Look at an image and return a text interpretation from the Gemini vision model. The calling agent supplies the prompt, so it controls exactly what the model should return (a description, OCR of visible text, a list of objects, structured JSON, etc.). Pass |
| list_modelsA | List the Gemini model ids available on the configured OpenAI-compatible endpoint. |
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 completely distinct purposes: describe_image processes images, while list_models enumerates available models. There is no overlap or ambiguity in their roles.
Both tools follow the identical verb_noun naming pattern (describe_image and list_models), creating a clear and predictable convention. This consistency makes the tool set easy to navigate.
With only 2 tools, the server is lean but appropriately scoped for its narrow purpose of explaining images. The core describe_image tool is supported by list_models, giving just enough functionality without bloat.
For the stated purpose of image explanation, the server fully covers the domain. describe_image is flexible via custom prompts, supporting descriptions, OCR, object listing, and more, with no obvious gaps for a single-purpose MCP server.