MCP Server Replicate
A FastMCP server implementation that facilitates resource-based access to AI model inference, focusing on image generation through the Replicate API, with features like real-time updates, webhook integration, and secure API key management.
gerred
Tools
generate_image
Generate an image using the specified parameters.
list_models
List available models on Replicate with optional filtering by owner.
search_models
Search for models using semantic search.
list_collections
List available model collections on Replicate.
get_collection_details
Get detailed information about a specific collection.
list_hardware
List available hardware options for running models.
list_templates
List all available templates with their schemas.
validate_template_parameters
Validate parameters against a template schema.
create_prediction
Create a new prediction using a specific model version on Replicate. Args: input: Model input parameters including version or model details confirmed: Whether the user has explicitly confirmed the generation Returns: Prediction details if confirmed, or a confirmation request if not
get_prediction
Get the status and results of a prediction.
cancel_prediction
Cancel a running prediction.
get_webhook_secret
Get the signing secret for verifying webhook requests.
verify_webhook
Verify that a webhook request came from Replicate using HMAC-SHA256. Args: payload: The webhook payload to verify signature: The signature from the X-Replicate-Signature header secret: The webhook signing secret from get_webhook_secret Returns: True if signature is valid, False otherwise
search_available_models
Search for available models matching the query. Args: query: Search query describing the desired model style: Optional style to filter by Returns: List of matching models with scores
get_model_details
Get detailed information about a specific model. Args: model_id: Model identifier in format owner/name Returns: Detailed model information
subscribe_to_generation
Handle resource subscription requests.
unsubscribe_from_generation
Handle resource unsubscribe requests.
open_image_with_system
Open an image URL with the system's default application. Args: image_url: URL of the image to open Returns: Dict containing status of the operation
README
MCP Server Replicate
A FastMCP server implementation for the Replicate API, providing resource-based access to AI model inference with a focus on image generation.
<a href="https://glama.ai/mcp/servers/r830bzsk7r"><img width="380" height="200" src="https://glama.ai/mcp/servers/r830bzsk7r/badge" alt="Server Replicate MCP server" /></a>
Features
- 🖼️ Resource-based image generation and management
- 🔄 Real-time updates through subscriptions
- 📝 Template-driven parameter configuration
- 🔍 Comprehensive model discovery and selection
- 🪝 Webhook integration for external notifications
- 🎨 Quality and style presets for optimal results
- 📊 Progress tracking and status monitoring
- 🔒 Secure API key management
Available Prompts
The server provides several specialized prompts for different tasks:
Text to Image (Primary)
Our most thoroughly tested and robust prompt. Optimized for generating high-quality images from text descriptions with:
- Detailed style control
- Quality presets (draft, balanced, quality, extreme)
- Size and aspect ratio customization
- Progress tracking and real-time updates
Example:
Create a photorealistic mountain landscape at sunset with snow-capped peaks, quality level: quality, style: photorealistic
Other Prompts
- Image to Image: Transform existing images (coming soon)
- Model Selection: Get help choosing the right model for your task
- Parameter Help: Understand and configure model parameters
Prerequisites
- Python 3.11 or higher
- A Replicate API key (get one at https://replicate.com/account)
- UV for dependency management
Installation
Installing via Smithery
To install MCP Server Replicate for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @gerred/mcp-server-replicate --client claude
Installing Manually
You can install the package directly from PyPI:
# Using UV (recommended)
uv pip install mcp-server-replicate
# Using UVX for isolated environments
uvx install mcp-server-replicate
# Using pip
pip install mcp-server-replicate
Claude Desktop Integration
- Make sure you have the latest version of Claude Desktop installed
- Open your Claude Desktop configuration:
# macOS
code ~/Library/Application\ Support/Claude/claude_desktop_config.json
# Windows
code %APPDATA%\Claude\claude_desktop_config.json
- Add the server configuration using one of these options:
{
"globalShortcut": "Shift+Alt+A",
"mcpServers": {
"replicate": {
"command": "uv",
"args": ["tool", "run", "mcp-server-replicate"],
"env": {
"REPLICATE_API_TOKEN": "APITOKEN"
},
"cwd": "$PATH_TO_REPO"
}
}
}
- Set your Replicate API key:
# Option 1: Set in your environment
export REPLICATE_API_TOKEN=your_api_key_here
# Option 2: Create a .env file in your home directory
echo "REPLICATE_API_TOKEN=your_api_key_here" > ~/.env
- Restart Claude Desktop completely
You should now see the 🔨 icon in Claude Desktop, indicating that the MCP server is available.
Usage
Once connected to Claude Desktop, you can:
-
Generate images with natural language:
Create a photorealistic mountain landscape at sunset with snow-capped peaks
-
Browse your generations:
Show me my recent image generations
-
Search through generations:
Find my landscape generations
-
Check generation status:
What's the status of my last generation?
Troubleshooting
Server not showing up in Claude Desktop
- Check the Claude Desktop logs:
tail -n 20 -f ~/Library/Logs/Claude/mcp*.log
- Verify your configuration:
- Make sure the path in
claude_desktop_config.json
is absolute - Ensure UV is installed and in your PATH
- Check that your Replicate API key is set
- Try restarting Claude Desktop
For more detailed troubleshooting, see our Debugging Guide.
Documentation
Development
- Clone the repository:
git clone https://github.com/gerred/mcp-server-replicate.git
cd mcp-server-replicate
- Install development dependencies:
uv pip install --system ".[dev]"
- Install pre-commit hooks:
pre-commit install
- Run tests:
pytest
Contributing
We welcome contributions! Please see our Contributing Guide for details.
License
This project is licensed under the MIT License - see the LICENSE file for details.
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