AI Image-Gen MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CACHE_DIR | No | Directory for caching generated images | /tmp/ai-image-gen-cache |
| MODEL_DEFAULT | No | Default model to use (dall-e-3, dall-e-2, or gpt-image-1) | dall-e-3 |
| OPENAI_API_KEY | Yes | Your OpenAI 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 | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageA | Generate images from text descriptions using AI models. Args: prompt: Text description of the desired image style: Style preset (default, photorealistic, illustration) size: Image dimensions (1024x1024, 1792x1024, 1024x1792) n: Number of images to generate (currently only 1 supported) model: Specific model to use (dalle-3, dalle-2, gpt-image-1) Returns: ImageGenerationResponse with image URLs and metadata |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| product_mockup | Generate a product mockup prompt. Args: product_name: Name of the product style: Visual style background: Background description Returns: Formatted prompt for product mockup generation |
| concept_art | Generate a concept art prompt. Args: subject: Main subject of the artwork art_style: Artistic style mood: Mood or atmosphere Returns: Formatted prompt for concept art generation |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| list_models | List available image generation models. Returns: Dictionary containing available models and their capabilities |
TDQS
Scored across 1 tool
With only one tool, there is no risk of ambiguity. The tool has a clear and distinct purpose.
The single tool name 'generate_image' follows a consistent verb_noun pattern, which is clear and predictable.
A single tool for an image generation server is borderline. While it covers the core function, the surface feels thin compared to typical MCP servers with 3-15 tools.
The server only provides a create operation (generate_image). Missing get, update, delete, or list capabilities for generated images, which are significant gaps for managing outputs.