This server allows you to generate images using text prompts with the following capabilities:
Create Custom Images: Generate images based on text descriptions
Customize Generation Parameters: Adjust settings like:
Width and height for image dimensions
Steps for generation quality
Seed for reproducible results
Guidance scale for prompt adherence
Negative prompts to exclude unwanted elements
Random string for additional variation
Integration: Seamlessly works with Cursor for development workflows
Output Format: Receive generated images as Base64 encoded data
Error Handling: Get informative messages and status codes for troubleshooting
Provides a Node.js runtime environment for the MCP server, with version 14.0.0 or higher required.
Enables installation and package management for the Draw Things MCP server.
Used for type definitions in the MCP tool integration, providing structured parameter typing for the generateImage function.
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., "@Draw Things MCP generate a cute cat playing with yarn"
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.
Draw Things API integration for Cursor using Model Context Protocol (MCP).
Node.js >= 14.0.0
Draw Things API running on http://127.0.0.1:7888
Related MCP server: Jira Context MCP Server
# Install globally
npm install -g draw-things-mcp-cursor
# Or run directly
npx draw-things-mcp-cursorTo set up this tool in Cursor, see the detailed guide in cursor-setup.md.
Quick setup:
Create or edit ~/.cursor/claude_desktop_config.json:
{
"mcpServers": {
"draw-things": {
"command": "draw-things-mcp-cursor",
"args": []
}
}
}Restart Cursor
Use in Cursor: generateImage({"prompt": "a cute cat"})
echo '{"prompt": "your prompt here"}' | npx draw-things-mcp-cursorprompt: The text prompt for image generation (required)
negative_prompt: The negative prompt for image generation
width: Image width (default: 360)
height: Image height (default: 360)
steps: Number of steps for generation (default: 8)
model: Model to use for generation (default: "flux_1_schnell_q5p.ckpt")
sampler: Sampling method (default: "DPM++ 2M AYS")
Example:
echo '{
"prompt": "a happy smiling dog, professional photography",
"negative_prompt": "ugly, deformed, blurry",
"width": 360,
"height": 360,
"steps": 4
}' | npx draw-things-mcp-cursorWhen used as an MCP tool in Cursor, the tool will be registered as generateImage with the following parameters:
{
prompt: string; // Required - The prompt to generate the image from
negative_prompt?: string; // Optional - The negative prompt
width?: number; // Optional - Image width (default: 360)
height?: number; // Optional - Image height (default: 360)
model?: string; // Optional - Model name
steps?: number; // Optional - Number of steps (default: 8)
}The generated images will be saved in the images directory with a filename format of:
<sanitized_prompt>_<timestamp>.png
Success:
{
"type": "success",
"content": [{
"type": "image",
"data": "base64 encoded image data",
"mimeType": "image/png"
}],
"metadata": {
"parameters": { ... }
}
}Error:
{
"type": "error",
"error": "error message",
"code": 500
}If you encounter issues:
Ensure Draw Things API is running at http://127.0.0.1:7888
Check log files in ~/.cursor/logs if using with Cursor
Make sure src/index.js has execution permissions: chmod +x src/index.js
MIT
Generate an image based on a prompt
Inputs: prompt, negative_prompt, width, height, +4 more.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 1 tool
With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'generateImage' has a distinct and clear purpose, so disambiguation is perfect.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'generateImage' follows a clear verb_noun pattern, and there are no other tools to compare it against for inconsistency.
A single tool for an image generation server feels thin and limited in scope. While it covers the core function, it lacks supporting operations like editing, listing, or managing images, making it borderline too few for a typical domain.
The server's purpose appears to be image generation, but with only a generate tool, there are significant gaps. There is no way to retrieve, update, delete, or manage generated images, which will likely cause agent failures in workflows requiring more than one-off generation.
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