Imagen MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| NEXOS_API_KEY | Yes | Your Nexos.ai API key for authentication |
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 |
|---|---|
| tasks | {
"list": {},
"cancel": {},
"requests": {
"tools": {
"call": {}
},
"prompts": {
"get": {}
},
"resources": {
"read": {}
}
}
} |
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_imageB | Generate a single image from a text prompt. Args: prompt: Text description of the image to generate. model: Model to use (imagen-4, imagen-4-fast, imagen-4-ultra, flux-1.1-pro, gpt-image-1). size: Image size (256x256, 512x512, 1024x1024, 1792x1024, 1024x1792). quality: Image quality (standard, hd). style: Image style (vivid, natural). Returns: Dictionary with success status, file path, and metadata. |
| start_image_batchA | Start generating multiple images and return the first one. This tool starts generating multiple images in the background. It blocks until the first image is ready, then returns it along with a session ID for retrieving the remaining images. Args: prompt: Text description of the image to generate. count: Number of images to generate (2-10). model: Model to use for generation. size: Image size. quality: Image quality (standard, hd). style: Image style (vivid, natural). Returns: Dictionary with session_id, first_image_path, and pending_count. |
| get_next_imageA | Get the next available image from a batch generation session. This tool retrieves the next image from an ongoing batch generation. If an image is already available, it returns immediately. Otherwise, it blocks until an image becomes available or timeout. Args: session_id: Session ID from start_image_batch. timeout: Maximum time to wait for an image (seconds, 1-300). Returns: Dictionary with file_path, has_more flag, and pending_count. |
| get_batch_statusA | Get the current status of a batch generation session. Args: session_id: Session ID from start_image_batch. Returns: Dictionary with session status, completed/pending counts, and errors. |
| list_modelsA | List all available image generation models with their descriptions. Returns a comprehensive list of all available models including:
Use this tool to discover which models are available and choose the best one for your image generation needs. Returns: Dictionary with models list and default model information. |
| get_model_detailsA | Get detailed information about a specific image generation model. Args: model_id: The model identifier (e.g., 'imagen-4', 'imagen-4-fast', 'dall-e-3'). Returns: Dictionary with complete model details including capabilities, rate limits, use cases, strengths, and weaknesses. Returns an error if the model is not found. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| models_catalog | Get the complete catalog of available image generation models. Returns a comprehensive list of all available models with their capabilities, rate limits, use cases, strengths, and weaknesses. |
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose with no ambiguity. generate_image creates single images, start_image_batch handles batch generation, get_next_image retrieves batch results, get_batch_status checks batch progress, list_models enumerates available models, and get_model_details provides specific model information. The tools cover different aspects of the image generation workflow without overlap.
All tools follow a consistent verb_noun pattern with snake_case throughout. The naming is predictable and readable: generate_image, start_image_batch, get_next_image, get_batch_status, list_models, and get_model_details. This consistency makes it easy for agents to understand the tool purposes from their names alone.
Six tools is well-scoped for an image generation server. Each tool earns its place by covering distinct aspects of the workflow: single generation, batch generation, batch retrieval, status checking, model listing, and model details. This count provides comprehensive coverage without being overwhelming or too sparse for the domain.
The tool surface provides complete coverage for image generation workflows. It supports both single and batch generation, includes status monitoring and result retrieval for batches, and offers comprehensive model discovery and information tools. There are no obvious gaps—agents can generate images, track progress, retrieve results, and make informed model selections.