Image Gen MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GEMINI_API_KEY | No | Gemini Developer API key. | |
| OPENAI_API_KEY | No | API key for OpenAI. | |
| VERTEX_PROJECT | No | GCP project id. | |
| VERTEX_LOCATION | No | GCP region (e.g., us-central1). | |
| OPENROUTER_API_KEY | No | OpenRouter API key. | |
| AZURE_OPENAI_API_KEY | No | Azure OpenAI key. | |
| AZURE_OPENAI_ENDPOINT | No | Azure endpoint URL. | |
| VERTEX_CREDENTIALS_PATH | No | Optional path to GCP JSON; ADC supported. | |
| AZURE_OPENAI_API_VERSION | No | Azure API version; default 2024-02-15-preview. | 2024-02-15-preview |
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
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageC | Generate image(s) from a text prompt. Prefer explicit provider+model; respect model capabilities. |
| edit_imageA | Edit an image with a prompt and optional mask. Pass images as data URLs/base64/https URLs. |
| get_model_capabilitiesA | Return enabled providers and per-model capability metadata (generation/edit/mask/limits). |
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 3 tools
Each tool has a clearly distinct purpose: generating images from text, editing existing images, and querying model capabilities. No overlap.
All tool names follow a consistent verb_noun pattern using snake_case (edit_image, generate_image, get_model_capabilities).
With only 3 tools, the server is minimal but covers the core operations for image generation and editing. The count is reasonable for a focused domain.
The tool set covers generate, edit, and model discovery. Missing operations like listing or deleting images are not critical, so the surface is mostly complete.