Image Generator MCP Server
# image-generator MCP Server
An mcp server that generates images based on image prompts
This is a TypeScript-based MCP server that implements image generation using **OPENAI**'s `dall-e-3` image generation model.
## Features
### Tools
- `generate_image` - Generate an image for given prompt
- Takes `prompt` as a required parameter
- Takes `imageName` as a required parameter to save the generated image in a `generated-images` directory on your desktop
## Development
Install dependencies:
```bash
npm install
```
Build the server:
```bash
npm run build
```
For development with auto-rebuild:
```bash
npm run watch
```
## Installation
To use with Claude Desktop, add the server config:
On MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`
```json
{
"mcpServers": {
"command": "image-generator",
"env": {
"OPENAI_API_KEY": "<your-openai-api-key>"
}
}
}
```
Make sure to replace `<your-openai-api-key>` with your actual **OPENAI** Api Key.
### Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector), which is available as a package script:
```bash
npm run inspector
```
The Inspector will provide a URL to access debugging tools in your browser.
TDQS
Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The tool's purpose is clearly defined and distinct by default.
The single tool name follows a clear verb_noun pattern (generate_image). Since there is only one tool, consistency is inherently perfect with no deviations.
A single tool is too few for a server named 'Image Generator MCP Server', which suggests a broader scope. This minimal set limits functionality and feels thin for image generation tasks that might benefit from variations or additional operations.
The tool surface is severely incomplete for image generation. It only offers generation from a prompt, with no obvious support for editing, resizing, style adjustments, or other common image operations, leading to significant gaps in agent workflows.