Gemini Image MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GOOGLE_API_KEY | Yes | Your Google AI API key for accessing Gemini AI services |
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageA | Create a new image using Google Gemini AI from a text description, optionally providing reference images to guide the result. Use the |
| edit_imageC | Modify an existing image using Google Gemini AI based on a text instruction. Provide the path to the image you want to edit and describe the changes that should be applied. |
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 clearly distinct purposes: generate_image creates new images from text descriptions, while edit_image modifies existing images based on text instructions. The descriptions explicitly differentiate them and even cross-reference when to use each, eliminating any potential confusion.
Both tools follow a consistent verb_noun pattern (generate_image, edit_image) with clear action verbs that accurately describe their functions. The naming is perfectly uniform and predictable across the tool set.
With only 2 tools, this server feels somewhat thin for an image generation/editing domain. While the tools cover the core operations, additional functionality like image analysis, format conversion, or batch processing might be expected but are absent, making the scope borderline minimal.
For a basic image AI server, the tools cover the essential create and modify operations well. However, there are minor gaps such as no direct image analysis or metadata tools, and the reliance on external paths for images might limit some workflows, though agents can generally work around these limitations.