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Ideogram MCP Server

@MCP-Mirror

Basic information

Category

Other

Transports

stdio

Author

MCP-Mirror

About Ideogram MCP Server

Mirror of

Ideogram MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Ideogram MCP Server tools

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This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

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Overview

What is Ideogram MCP Server?

The Ideogram MCP Server is a Model Context Protocol (MCP) server that provides image generation capabilities using the Ideogram API. It allows users to generate images from text prompts with customizable parameters such as aspect ratio, model selection, and style.

How to use Ideogram MCP Server?

Install dependencies with npm install, set your Ideogram API key in an .env file as IDEOGRAM_API_KEY, build the project with npm run build, and optionally link globally with npm link. The server exposes the generate_image tool which can be invoked via an MCP client.

Key features of Ideogram MCP Server

  • Generate images from text prompts
  • Customize aspect ratio, model, and style
  • Enable or disable magic prompt option
  • Set negative prompts to exclude elements
  • Generate 1–8 images per request

Use cases of Ideogram MCP Server

  • Create visuals from detailed text descriptions
  • Generate images in specific aspect ratios for social media or presentations
  • Experiment with different Ideogram models and generation styles
  • Produce multiple image variants for rapid prototyping

Frequently asked questions

1

What do I need to run this server?

You need Node.js, npm, and a valid Ideogram API key set in the `IDEOGRAM_API_KEY` environment variable.

2

How do I use the generate_image tool?

The tool is called via an MCP client. You must provide a `prompt` and can optionally set `aspect_ratio`, `model`, `magic_prompt_option`, `style_type`, `negative_prompt`, and `num_images`.

3

Is there a limit on how many images I can generate at once?

Yes, the `num_images` parameter accepts values between 1 and 8.

4

Which models are available?

The server supports `V_1`, `V_1_TURBO`, `V_2`, and `V_2_TURBO`.

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