Ideogram MCP Server
Click on "Deploy 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 Server Generate a realistic portrait of a cat wearing a hat"
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
A Model Context Protocol (MCP) server implementation for the Ideogram AI API. This server provides tools for generating, editing, and describing images using Ideogram's powerful AI models.
Features
Generate images from text descriptions
Edit existing images using masks
Generate descriptions for images
Download generated images to local directory
Prompt templates for common operations
Related MCP server: Replicate Ideogram V3 MCP Server
Installation
Clone the repository
git clone https://github.com/flowluap/ideogram-mcp-server.git
cd ideogram-mcp-serverInstall dependencies
npm installBuild the project
npm run buildCursor Integration
To use this MCP in Cursor, add the following configuration to your Cursor settings (Settings > AI > Model Context Protocol):
{
"mcps": {
"ideogram-mcp": {
"command": "node",
"args": ["PATH_TO_YOUR_DIST/index.js"],
"env": {
"IDEOGRAM_API_KEY": "your-api-key-here"
}
}
}
}Replace:
PATH_TO_YOUR_DIST/index.jswith the absolute path to your builtindex.jsfileyour-api-key-herewith your actual Ideogram API key
Example (redacted):
{
"mcps": {
"ideogram-mcp": {
"command": "node",
"args": ["/path/to/ideogram-mcp-server/dist/index.js"],
"env": {
"IDEOGRAM_API_KEY": "xxxxx-REDACTED-xxxxx"
}
}
}
}Available Tools
generateGenerate images from text prompts
Parameters:
prompt: string (required)aspect_ratio: string (optional) - One of: ASPECT_1_1, ASPECT_16_9, ASPECT_9_16, ASPECT_4_3, ASPECT_3_4model: string (optional) - One of: V_1, V_2, V_2_TURBOmagic_prompt_option: string (optional) - One of: AUTO, ON, OFFnum_images: number (optional) - Between 1 and 8seed: number (optional) - Between 0 and 2147483647
editEdit images using masks
Parameters:
image_file: string (required) - Base64 or file pathmask: string (required) - Base64 or file pathprompt: string (required)model: string (required) - One of: V_2, V_2_TURBO
describeGenerate descriptions for images
Parameters:
image_file: string (required) - Base64 or file path
download_imagesDownload generated images to local directory
Parameters:
urls: string[] (required) - Array of image URLsoutput_dir: string (required) - Output directory path
Prompt Templates
generate_imageTemplate for generating images
Parameters:
description: string
Development
# Build the project
npm run build
# Run in development mode
npm run dev
# Run tests
npm test
# Run linter
npm run lintRequirements
Node.js >= 18.0.0
Ideogram API key
License
This project is licensed under the MIT License - see the LICENSE file for details.
Contributing
Fork the repository
Create your feature branch
Commit your changes
Push to the branch
Create a new Pull Request
Available Tools
4 toolsdescribeD
Inputs: image_file (required).
download_imagesD
Inputs: urls (required), output_dir (required).
editD
Inputs: image_file (required), mask (required), prompt (required), model (required).
generateD
Inputs: prompt (required), aspect_ratio, model, magic_prompt_option, +2 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Tool names are distinct (describe, download_images, edit, generate) but without descriptions, an agent cannot reliably determine their boundaries. For example, 'describe' might overlap with 'generate' if generating a description, leading to potential misselection.
Naming is inconsistent: 'describe', 'edit', and 'generate' are single verbs, while 'download_images' uses a verb_noun pattern with an underscore. No consistent verb_noun or camelCase pattern is followed.
4 tools is within the typical well-scoped range (3-15), but for an image generation server, the set feels slightly thin. Still, each tool appears to serve a distinct purpose without being excessive.
The tools cover basic operations: generate, edit, describe, and download images. However, obvious gaps exist, such as missing list, delete, or style-transfer tools, which may cause agent failures in common workflows.
Maintenance
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Related MCP Servers
- AlicenseNot gradedqualityNot gradedmaintenanceEnables high-quality AI image generation with superior text rendering using the fal-ai/ideogram/v3 model. Supports advanced style control, custom dimensions, color palettes, reference images, and queue-based generation with automatic local image downloads.-
- AlicenseBqualityNot gradedmaintenanceEnables AI-powered image generation using the Ideogram V3 Balanced model via Replicate. Supports text-to-image generation, inpainting, style transfer with 60+ presets, custom resolutions, and reproducible outputs with local image storage.2-
- AlicenseAqualityDmaintenanceProvides image generation, modification, and analysis capabilities using Google's Gemini API, enabling AI-powered image operations through natural language.5128 npmMIT
- AlicenseNot gradedqualityDmaintenanceEnables LLM applications to generate, edit, describe, upscale, remix, reframe, and replace backgrounds in images using the Ideogram AI API.30 npmMIT