Navigation
Mavae Image Toolbox: Pro Editing & Model Mastery - MCP Implementation

Mavae Image Toolbox: Pro Editing & Model Mastery

Mavae Image Toolbox: The MCP server artists craveβ€”generate, edit, curate collections, and master models/LoRas like a pro. Your visual empire, streamlined. πŸš€

✨ Developer Tools
4.3(125 reviews)
187 saves
87 comments

Ranked in the top 8% of all AI tools in its category

About Mavae Image Toolbox

What is Mavae Image Toolbox: Pro Editing & Model Mastery?

Mavae Image Toolbox is a Model Context Protocol (MCP) server designed to streamline AI-driven image creation, editing, and resource management. It acts as a standardized interface for AI agents to interact with advanced tools for generating, manipulating, and organizing image-based workflows. Whether you're building creative applications or automating image tasks, this toolkit provides robust capabilities to handle everything from model management to real-time image adjustments.

How to Use Mavae Image Toolbox: Pro Editing & Model Mastery?

Follow these core steps to activate and configure the system:

  1. Installation: Install dependencies via npm install, then compile the project using npm run build.
  2. Server Setup: Launch with npm start and ensure the MAVAE_API_KEY environment variable is set.
  3. MCP Configuration: Define the server in your MCP JSON file, pointing to the compiled dist/index.js.
  4. Docker Option: Build and run the container with docker build and docker run, passing your API key via environment variables.

Mavae Image Toolbox Features

Key Features of Mavae Image Toolbox: Pro Editing & Model Mastery?

  • Advanced Image Generation: Supports both raw parameter-based creation and collection-driven templates, with retry mechanisms for failed tasks.
  • Efficient Editing: Perform lossless compression and customizable cropping, compatible with local files and URLs.
  • Resource Control: Manage Loras, models, and image assets through dedicated APIs. Query real-time statuses of generations and collections.
  • Collaboration Tools: Create public or private collections for sharing configurations, ensuring consistent output across teams.
  • Security & Compliance: API token management with authentication safeguards to protect sensitive operations.

Use Cases of Mavae Image Toolbox: Pro Editing & Model Mastery?

Common applications include:

  • Design Automation: Scale product mockups or asset generation for e-commerce platforms using predefined style collections.
  • AI Workflow Integration: Embed image editing into larger applications (e.g., cropping user-uploaded images before storage).
  • Model Testing: Compare outputs from different Loras or base models without manual configuration.
  • Batch Processing: Process large datasets for tasks like image optimization or content categorization.

Mavae Image Toolbox FAQ

FAQ from Mavae Image Toolbox: Pro Editing & Model Mastery?

How do I obtain an API key?
Apply via the official portal here, ensuring your account is verified.
Can I use relative paths for image editing?
Paths must be absolute when running locally. For Docker setups, mount directories to avoid path discrepancies.
What if my image generation task fails?
Use the image_retry_generate tool with the original task ID to reprocess failed requests.
How do I update my model list?
Restart the server after new models are available, or refresh the cache via the list_models endpoint.
Is there a cost for collection sharing?
Public collections are free to share, but API usage charges apply to generation/editing operations.

Content

MAVAE - IMAGE TOOLBOX

A powerful creative and editing toolkit designed for AI Agents.

smithery badge TypeScript Node.js MCP Docker

MAVAE is a Model Context Protocol (MCP) server for interacting with image media tools. It provides a standardized interface for AI Agents to generate and manipulate images.

πŸš€ Features

  • Image Generation : Generate images using both raw configurations and predefined collections
  • Image Editing : Compress and crop images
  • Collection Management : Create, manage, and share configurations for consistent image generation
  • Model & Lora Management: List and utilize available models and Loras
  • API Token Management : Handle authentication for secure interaction with Mavae services

πŸ“‹ Prerequisites

  • Node.js (v16 or higher)
  • MAVAE API Key (set as environment variable, Apply here)

πŸ› οΈ Installation

# Install dependencies
npm install

# Build the project
npm run build

# Start the server
npm start

MCP Json

{
  "mcpServers": {
      "mavae": {
          "command": "node",
          "args": [
              "***/dist/index.js"
          ],
          "env": {
              "MAVAE_API_KEY": MAVAE_API_KEY
          }
      }
  }
}

When using MAVAE MCP locally, this path is an absolute path πŸ‘‰πŸ» "***/dist/index.js"

🐳 Docker Support

# Build Docker image
docker build -t mavae-mcp-server .

# Run Docker container
docker run -e MAVAE_API_KEY=your_api_key mavae-mcp-server

πŸ“ Project Structure

mavae/
β”œβ”€β”€ src/                  # Source code
β”‚   β”œβ”€β”€ actions/          # API endpoint implementation handlers
β”‚   β”‚   β”œβ”€β”€ aigc.ts       # Image generation operations
β”‚   β”‚   β”œβ”€β”€ collection.ts # Collection management operations
β”‚   β”‚   β”œβ”€β”€ edit.ts       # Image editing operations
β”‚   β”‚   └── token.ts      # API token operations
β”‚   β”œβ”€β”€ tools/            # MCP tool definitions
β”‚   β”‚   β”œβ”€β”€ aigc.ts       # Image generation tool definitions
β”‚   β”‚   β”œβ”€β”€ collection.ts # Collection management tool definitions
β”‚   β”‚   └── edit.ts       # Image editing tool definitions
β”‚   β”œβ”€β”€ types/            # TypeScript type definitions
β”‚   β”‚   β”œβ”€β”€ aigc.ts       # Image generation types
β”‚   β”‚   β”œβ”€β”€ collection.ts # Collection types
β”‚   β”‚   β”œβ”€β”€ edit.ts       # Image editing types
β”‚   β”‚   └── response.ts   # API response types
β”‚   β”œβ”€β”€ utils/            # Utility functions
β”‚   β”‚   └── constants.ts  # Constant values
β”‚   └── index.ts          # Server entry point
β”œβ”€β”€ dist/                 # Compiled JavaScript files
β”œβ”€β”€ package.json          # Project dependencies and scripts
└── tsconfig.json         # TypeScript configuration

πŸ›οΈ Available Tools

Image Generation

  • image_raw_generate - Generate an image using raw AIGC configuration
  • image_collection_generate - Generate an image using a collection's AIGC configuration
  • image_retry_generate - Retry a failed image generation
  • image_state - Get the details of an owned image
  • generate_task_state - Get the generation state of an image by task id

Collection Management

  • collection_create - Create a new collection
  • collection_delete - Delete a collection
  • collection_toggle_public - Toggle the public status of a collection
  • collection_list - Get the list of owned collections
  • collection_state - Get the details of an owned collection

Image Editing

  • compress_image - Lossless compression of images
  • crop_image - Crop images with local path and URL support

Model & Resources

  • list_images - Get the list of owned images
  • list_loras - Get the list of available loras
  • list_models - Get the list of available models

Authentication

  • token_state - Get the x-api-token state

Related MCP Servers & Clients