Provides tools for generating images through Replicate's Flux 1.1 Pro model, allowing for customization of aspect ratios, output formats, and safety settings.
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., "@Replicate Designer MCPcreate a 16:9 image of a futuristic library with bioluminescent plants"
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.
Replicate Designer MCP
An MCP server for generating images using Replicate's Flux 1.1 Pro model.
Installation
Using Directly from GitHub
You can use the MCP server directly from GitHub in several ways:
Option 1: Install directly with pip
pip install git+https://github.com/yourusername/replicate-designer.gitThen run it with:
mcp-replicate-designerOption 2: Use npx with GitHub repository
Create a configuration file (e.g., mcps.json):
{
"mcpServers": {
"replicateDesigner": {
"command": "npx",
"args": [
"-y",
"github:yourusername/replicate-designer"
],
"env": {
"REPLICATE_API_TOKEN": "your_replicate_api_token_here"
}
}
}
}Then use it with Claude or another assistant:
npx @anthropic-ai/assistant --mcps-json mcps.jsonThis method allows you to include your Replicate API token directly in the configuration file, which is more convenient than setting environment variables separately.
Option 3: Local Installation
Clone the repository and install from the local directory:
git clone https://github.com/yourusername/replicate-designer.git
cd replicate-designer
pip install -e .Publishing and Using via npm
To make your MCP available via npm (for easier distribution):
Package and publish your MCP:
# Build a wheel
pip install build
python -m build
# Publish to npm (after setting up an npm account)
npm init
npm publishThen users can install and use it directly:
npx -y mcp-replicate-designerUsage
Setting the API Token
There are several ways to provide your Replicate API token:
Environment variable (for command line usage):
export REPLICATE_API_TOKEN=your_api_token_hereIn the MCP configuration file (as shown in Option 2 above):
{ "mcpServers": { "replicateDesigner": { "command": "...", "args": ["..."], "env": { "REPLICATE_API_TOKEN": "your_replicate_api_token_here" } } } }Using a .env file in your project directory:
REPLICATE_API_TOKEN=your_api_token_hereThen, install the python-dotenv package:
pip install python-dotenv
Security Note: Be careful with your API tokens. Never commit them to public repositories, and use environment variables or secure secret management when possible.
Running the MCP server
mcp-replicate-designerBy default, it runs in stdio mode which is compatible with npx use. You can also run it in SSE mode:
mcp-replicate-designer --transport sse --port 8000Using with npx
This MCP can be used with an AI agent using npx in two ways:
Direct command line
npx @anthropic-ai/assistant --mcp mcp-replicate-designerAs a configuration object
In your configuration JSON:
{
"mcpServers": {
"replicateDesigner": {
"command": "npx",
"args": [
"-y",
"mcp-replicate-designer"
]
}
}
}Then use it with:
npx @anthropic-ai/assistant --mcps-json /path/to/your/config.jsonTool
This MCP exposes a single tool:
generate_image
Generates an image using Replicate's Flux 1.1 Pro model.
Parameters:
prompt(string, required): Text description of the image to generateaspect_ratio(string, optional, default: "1:1"): Aspect ratio for the generated imageoutput_format(string, optional, default: "webp"): Format of the output imageoutput_quality(integer, optional, default: 80): Quality of the output image (1-100)safety_tolerance(integer, optional, default: 2): Safety tolerance level (0-3)prompt_upsampling(boolean, optional, default: true): Whether to use prompt upsampling
Example:
{
"prompt": "A photograph of an humanoid AI agent looking sad and in disrepair, the agent is sat at a workbench getting fixed by a human male",
"aspect_ratio": "1:1",
"output_format": "webp"
}Resources
Looking for Admin?
Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.