Replicate Flux

Replicate Flux

awkoy

Connects to Replicate's Flux and Recraft models to generate high-quality raster images and vector graphics through conversation interfaces.

Integrates with Replicate's Flux image generation model, enabling image creation capabilities within conversation interfaces through a simple API token setup and TypeScript implementation available as both an npm module and Docker container.

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What it does

  • Generate raster images using Flux Schnell model
  • Create vector graphics with Recraft V3 SVG model
  • Integrate image generation into chat interfaces
  • Configure custom image generation parameters

Best for

AI assistants needing image generation capabilitiesDevelopers building creative tools with conversational interfacesApplications requiring both raster and vector graphic creation
Supports both raster and vector image generationAvailable as npm package and Docker container

About Replicate Flux

Replicate Flux is a community-built MCP server published by awkoy that provides AI assistants with tools and capabilities via the Model Context Protocol. Replicate Flux is an OpenAPI image generator using Replicate's Flux model, enabling image creation via API and TypeScrip It is categorized under ai ml.

How to install

You can install Replicate Flux in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

Replicate Flux is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

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Replicate Flux MCP

MCP Compatible License TypeScript Model Context Protocol smithery badge NPM Downloads Stars

README image Link to glama.ai

Replicate Flux MCP is an advanced Model Context Protocol (MCP) server that empowers AI assistants to generate high-quality images and vector graphics. Leveraging Black Forest Labs' Flux Schnell model for raster images and Recraft's V3 SVG model for vector graphics via the Replicate API.

πŸ“‘ Table of Contents

πŸš€ Getting Started & Integration

Setup Process

  1. Obtain a Replicate API Token

    • Sign up at Replicate
    • Create an API token in your account settings
  2. Choose Your Integration Method

    • Follow one of the integration options below based on your preferred MCP client
  3. Ask Your AI Assistant to Generate an Image

    • Simply ask naturally: "Can you generate an image of a serene mountain landscape at sunset?"
    • Or be more specific: "Please create an image showing a peaceful mountain scene with a lake reflecting the sunset colors in the foreground"
  4. Explore Advanced Features

    • Try different parameter settings for customized results
    • Experiment with SVG generation using generate_svg
    • Use batch image generation or variant generation features

Cursor Integration

Method 1: Using mcp.json

  1. Create or edit the .cursor/mcp.json file in your project directory:
{
  "mcpServers": {
    "replicate-flux-mcp": {
      "command": "env REPLICATE_API_TOKEN=YOUR_TOKEN npx",
      "args": ["-y", "replicate-flux-mcp"]
    }
  }
}
  1. Replace YOUR_TOKEN with your actual Replicate API token
  2. Restart Cursor to apply the changes

Method 2: Manual Mode

  1. Open Cursor and go to Settings
  2. Navigate to the "MCP" or "Model Context Protocol" section
  3. Click "Add Server" or equivalent
  4. Enter the following command in the appropriate field:
env REPLICATE_API_TOKEN=YOUR_TOKEN npx -y replicate-flux-mcp
  1. Replace YOUR_TOKEN with your actual Replicate API token
  2. Save the settings and restart Cursor if necessary

Claude Desktop Integration

  1. Create or edit the mcp.json file in your configuration directory:
{
  "mcpServers": {
    "replicate-flux-mcp": {
      "command": "npx",
      "args": ["-y", "replicate-flux-mcp"],
      "env": {
        "REPLICATE_API_TOKEN": "YOUR TOKEN"
      }
    }
  }
}
  1. Replace YOUR_TOKEN with your actual Replicate API token
  2. Restart Claude Desktop to apply the changes

Smithery Integration

This MCP server is available as a hosted service on Smithery, allowing you to use it without setting up your own server.

  1. Visit Smithery and create an account if you don't have one
  2. Navigate to the Replicate Flux MCP server page
  3. Click "Add to Workspace" to add the server to your Smithery workspace
  4. Configure your MCP client (Cursor, Claude Desktop, etc.) to use your Smithery workspace URL

For more information on using Smithery with your MCP clients, visit the Smithery documentation.

Glama.ai Integration

This MCP server is also available as a hosted service on Glama.ai, providing another option to use it without local setup.

  1. Visit Glama.ai and create an account if you don't have one
  2. Go to the Replicate Flux MCP server page
  3. Click "Install Server" to add the server to your workspace
  4. Configure your MCP client to use your Glama.ai workspace

For more information, visit the Glama.ai MCP servers documentation.

🌟 Features

  • πŸ–ΌοΈ High-Quality Image Generation - Create stunning images using Flux Schnell, a state-of-the-art AI model
  • 🎨 Vector Graphics Support - Generate professional SVG vector graphics with Recraft V3 SVG model
  • πŸ€– AI Assistant Integration - Seamlessly enable AI assistants like Claude to generate visual content
  • πŸŽ›οΈ Advanced Customization - Fine-tune generation with controls for aspect ratio, quality, resolution, and more
  • πŸ”Œ Universal MCP Compatibility - Works with all MCP clients including Cursor, Claude Desktop, Cline, and Zed
  • πŸ”’ Secure Local Processing - All requests are processed locally for enhanced privacy and security
  • πŸ” Comprehensive History Management - Track, view, and retrieve your complete generation history
  • πŸ“Š Batch Processing - Generate multiple images from different prompts in a single request
  • πŸ”„ Variant Exploration - Create and compare multiple interpretations of the same concept
  • ✏️ Prompt Engineering - Fine-tune image variations with specialized prompt modifications

πŸ“š Documentation

Available Tools

generate_image

Generates an image based on a text prompt using the Flux Schnell model.

{
  prompt: string;                // Required: Text description of the image to generate
  seed?: number;                 // Optional: Random seed for reproducible generation
  go_fast?: boolean;             // Optional: Run faster predictions with optimized model (default: true)
  megapixels?: "1" | "0.25";     // Optional: Image resolution (default: "1")
  num_outputs?: number;          // Optional: Number of images to generate (1-4) (default: 1)
  aspect_ratio?: string;         // Optional: Aspect ratio (e.g., "16:9", "4:3") (default: "1:1")
  output_format?: string;        // Optional: Output format ("webp", "jpg", "png") (default: "webp")
  output_quality?: number;       // Optional: Image quality (0-100) (default: 80)
  num_inference_steps?: number;  // Optional: Number of denoising steps (1-4) (default: 4)
  disable_safety_checker?: boolean; // Optional: Disable safety filter (default: false)
}

generate_multiple_images

Generates multiple images based on an array of prompts using the Flux Schnell model.

{
  prompts: string[];             // Required: Array of text descriptions for images to generate (1-10 prompts)
  seed?: number;                 // Optional: Random seed for reproducible generation
  go_fast?: boolean;             // Optional: Run faster predictions with optimized model (default: true)
  megapixels?: "1" | "0.25";     // Optional: Image resolution (default: "1")
  aspect_ratio?: string;         // Optional: Aspect ratio (e.g., "16:9", "4:3") (default: "1:1")
  output_format?: string;        // Optional: Output format ("webp", "jpg", "png") (default: "webp")
  output_quality?: number;       // Optional: Image quality (0-100) (default: 80)
  num_inference_steps?: number;  // Optional: Number of denoising steps (1-4) (default: 4)
  disable_safety_checker?: boolean; // Optional: Disable safety filter (default: false)
}

generate_image_variants

Generates multiple variants of the same image from a single prompt.

{
  prompt: string;                // Required: Text description for the image to generate variants of
  num_variants: number;          // Required: Number of image variants to generate (2-10, default: 4)
  prompt_variations?: string[];  // Optional: List of prompt modifiers to apply to variants (e.g., ["in watercolor style", "in oil painting style"])
  variation_mode?: "append" | "replace"; // Optional: How to apply variations - 'append' adds to base prompt, 'replace' uses variations directly (default: "append")
  seed?: number;                 // Optional: Base random seed. Each variant will use seed+variant_index
  go_fast?: boolean;             // Optional: Run faster predictions with optimized model (default: true)
  megapixels?: "1" | "0.25";     // Optional: Image resolution (default: "1")
  aspect_ratio?: string;         // Optional: Aspect ratio (e.g., "16:9", "4:3") (default: "1:1")
  output_format?: string;        // Optional: Output format ("webp", "jpg", "png") (default: "webp")
  output_quality?: number;       // Optional: Image quality (0-100) (default: 80)
  num_inference_steps?: number;  // Optional: Number of denoising steps (1-4) (default: 4)
  disable_safety_checker?: boolean; // Optional: Disable safety filter (default: false)
}

generate_svg

Generates an SVG vector image based on a text prompt using the Recraft V3 SVG model.

{
  prompt: string;                // Required: Text description of the SVG to generate
  size?: string;                 // Optional: Size of the generated SVG (default: "1024x1024")
  sty

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*README truncated. [View full README on GitHub](https://github.com/awkoy/replicate-flux-mcp).*

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