ideogram-mcp-server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@ideogram-mcp-servergenerate a photorealistic image of a golden retriever puppy playing in a field of flowers"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Ideogram MCP Server
Warning: This is an unofficial, community-driven project and is not affiliated with, endorsed by, or sponsored by Ideogram AI. For official Ideogram resources, please visit ideogram.ai.
Note: This project was entirely implemented by an AI agent (Claude) using the auto-claude autonomous development system. The codebase, tests, and documentation were all generated through AI-assisted development. Human oversight was provided for requirements and review.
A production-grade Model Context Protocol (MCP) server that provides seamless integration between LLM applications (Claude Desktop, Cursor, VS Code) and the Ideogram AI image generation API. Powered by Ideogram V3, it offers 10 tools for complete image generation, editing, and analysis workflows.

What's New in v3.0.0
5 New Tools -- Describe, Upscale, Remix, Reframe, and Replace Background (10 tools total)
Character Reference Support -- Maintain visual consistency of characters across generations (generate, edit, remix)
Ideogram V3 API -- Edit tool migrated from legacy API to V3 with rendering speed control
Reframe replaces Outpainting -- Intelligent outpainting is now a dedicated tool with resolution targeting
Related MCP server: ImaginePro MCP Server
Features
Image Generation - Generate high-quality AI images from text prompts using Ideogram V3
Image Editing - Mask-based inpainting to edit specific parts of images (V3 API)
Image Description - Analyze images and generate detailed text descriptions
Image Upscaling - Enhance image resolution with guided upscaling controls
Image Remixing - Transform images with new prompts while preserving original characteristics
Image Reframing - Extend images to new resolutions via intelligent outpainting
Background Replacement - Automatically replace backgrounds while preserving foreground subjects
Character References - Maintain character consistency across multiple generations
Async Support - Queue generation requests for background processing
Cost Tracking - Estimated credit and USD costs included in all responses
Local Storage - Automatically save generated images locally (URLs expire)
Enterprise Error Handling - User-friendly messages with retry guidance
Type Safety - Full TypeScript strict mode with Zod validation
Quick Start
Prerequisites
Node.js 18+
Installation
# Clone the repository
git clone https://github.com/takeshijuan/ideogram-mcp-server.git
cd ideogram-mcp-server
# Install dependencies
npm install
# Build
npm run buildConfiguration
Create a .env file (or set environment variables):
# Required
IDEOGRAM_API_KEY=your_ideogram_api_key_here
# Optional
LOG_LEVEL=info # debug, info, warn, error
LOCAL_SAVE_DIR=./ideogram_images # Where to save images
ENABLE_LOCAL_SAVE=true # Auto-download generated imagesClaude Desktop Setup
Add to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"ideogram": {
"command": "node",
"args": ["/path/to/ideogram-mcp-server/dist/index.js"],
"env": {
"IDEOGRAM_API_KEY": "your_api_key_here"
}
}
}
}Restart Claude Desktop to load the server.
Available Tools (10)
ideogram_generate
Generate images from text prompts.
// Basic usage
{
prompt: "A beautiful sunset over mountains"
}
// With all options
{
prompt: "A cute cat wearing a wizard hat",
aspect_ratio: "16x9", // 15 ratios: 1x1, 16x9, 9x16, 4x3, 3x4, etc.
num_images: 4, // 1-8 images
rendering_speed: "QUALITY", // FLASH, TURBO, DEFAULT, QUALITY
magic_prompt: "ON", // AUTO, ON, OFF - enhance prompts
style_type: "REALISTIC", // AUTO, GENERAL, REALISTIC, DESIGN, FICTION
character_reference_images: ["https://example.com/char.jpg"],
save_locally: true // Save to local disk
}Response includes:
Image URLs and local paths (if saved)
Seeds for reproducibility
Cost estimates (credits and USD)
ideogram_edit
Edit specific parts of existing images using mask-based inpainting (V3 API).
// Edit parts of an image using a mask
{
prompt: "Add a red balloon in the sky",
image: "https://example.com/photo.jpg", // URL, file path, or base64 data URL
mask: maskImageData, // Black pixels=edit, White pixels=preserve
rendering_speed: "DEFAULT", // FLASH, TURBO, DEFAULT, QUALITY
character_reference_images: ["https://example.com/char.jpg"],
num_images: 1,
magic_prompt: "AUTO",
style_type: "AUTO"
}Mask Requirements:
Same dimensions as source image
Black and white pixels only (black=areas to edit, white=areas to preserve)
Black area must be at least 10% of total image
Supported formats: PNG, JPEG, WebP
ideogram_describe
Generate text descriptions from images.
{
image: "https://example.com/photo.jpg", // URL, file path, or base64
describe_model_version: "V_3" // "V_2" or "V_3" (default)
}
// Returns: array of text descriptionsideogram_upscale
Upscale images to higher resolution.
{
image: "https://example.com/photo.jpg",
prompt: "High detail landscape", // Optional guided upscaling
resemblance: 70, // 0-100: similarity to original (default 50)
detail: 80, // 0-100: detail enhancement level (default 50)
magic_prompt: "ON",
num_images: 1,
save_locally: true
}ideogram_remix
Remix images with a new text prompt.
{
image: "https://example.com/photo.jpg",
prompt: "Transform into a watercolor painting",
image_weight: 60, // 0-100: influence of original image (default 50)
aspect_ratio: "16x9",
rendering_speed: "QUALITY",
style_type: "FICTION",
character_reference_images: ["https://example.com/char.jpg"],
save_locally: true
}ideogram_reframe
Extend images to new resolutions via intelligent outpainting.
{
image: "https://example.com/square-photo.jpg",
resolution: "1920x1080", // Target resolution (required)
rendering_speed: "DEFAULT",
num_images: 1,
save_locally: true
}ideogram_replace_background
Replace image backgrounds while preserving foreground subjects.
{
image: "https://example.com/portrait.jpg",
prompt: "A tropical beach at sunset", // Describe the new background
magic_prompt: "ON",
rendering_speed: "QUALITY",
num_images: 4,
save_locally: true
}
// No mask needed - AI auto-detects foregroundideogram_generate_async
Queue generation requests for background processing.
{
prompt: "A complex scene with many details",
num_images: 8
}
// Returns immediately with prediction_id
// Poll with ideogram_get_predictionideogram_get_prediction
Check status and retrieve results of async requests.
{
prediction_id: "pred_abc123..."
}
// Returns: status (queued/processing/completed/failed)
// When completed: includes images and costideogram_cancel_prediction
Cancel queued async requests (before processing starts).
{
prediction_id: "pred_abc123..."
}
// Only works for predictions in 'queued' statusCost Tracking
All generation responses include estimated cost information:
{
"total_cost": {
"credits_used": 8,
"estimated_usd": 0.08,
"note": "Cost estimate based on known Ideogram pricing"
}
}Note: Costs are estimated locally based on known pricing. The Ideogram API does not return actual cost information.
Development
# Development with hot reload
npm run dev
# Run tests
npm test
# Run tests with coverage
npm run test:coverage
# Type checking
npm run typecheck
# Lint
npm run lint
# Format code
npm run format
# Test with MCP Inspector
npm run inspectProject Structure
ideogram-mcp-server/
├── src/
│ ├── index.ts # Entry point
│ ├── server.ts # MCP server setup
│ ├── config/ # Configuration
│ ├── services/ # Core services
│ │ ├── ideogram.client.ts # API client
│ │ ├── cost.calculator.ts # Cost estimation
│ │ ├── prediction.store.ts # Async job queue
│ │ └── storage.service.ts # Local file storage
│ ├── tools/ # MCP tools (10 tools)
│ │ ├── generate.ts
│ │ ├── generate-async.ts
│ │ ├── edit.ts
│ │ ├── describe.ts
│ │ ├── upscale.ts
│ │ ├── remix.ts
│ │ ├── reframe.ts
│ │ ├── replace-background.ts
│ │ ├── get-prediction.ts
│ │ └── cancel-prediction.ts
│ ├── types/ # TypeScript types
│ └── utils/ # Utilities
├── docs/ # Additional documentation
├── dist/ # Built output
└── package.jsonSecurity
API keys are passed via environment variables, never stored in code
All inputs validated with Zod schemas
File operations restricted to configured directories
No sensitive data logged
Contributing
Contributions are welcome! Please read our Contributing Guide for details on:
Development setup
Coding standards
Testing requirements
Pull request process
Quick start:
Fork the repository
Create a feature branch (
git checkout -b feature/amazing-feature)Commit your changes (
git commit -m 'Add amazing feature')Push to the branch (
git push origin feature/amazing-feature)Open a Pull Request
License
MIT License - see LICENSE for details.
Star History
Resources
API Reference - Complete documentation for all 10 tools
Built with love for the AI developer community
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Maintenance
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