mcp-flux-schnell
Integrates with Cloudflare's Flux Schnell worker API to provide text-to-image generation capabilities through MCP.
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., "@mcp-flux-schnell generate an image of a futuristic city with flying cars at sunset"
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.
mcp-flux-schnell MCP Server
A TypeScript-based MCP server that implements a text-to-image generation tool using the Flux Schnell model. This server integrates with Cloudflare's Flux Schnell worker API to provide image generation capabilities through MCP.
Creating your own Flux Schnell MCP Server is so easy! — Part 1
Creating your own Flux Schnell MCP Server is so easy! — Part 2
Features
Tools
generate_image- Generate images from text descriptionsTakes a text prompt as input (1-2048 characters)
Returns the path to the generated image file
Related MCP server: Image Generator MCP Server
Environment Variables
The following environment variables must be configured:
FLUX_API_URL- The URL of the Flux Schnell API endpointFLUX_API_TOKEN- Your authentication token for the Flux Schnell APIWORKING_DIR(optional) - Directory where generated images will be saved (defaults to current working directory)
Development
Install dependencies:
npm install
# or
pnpm installBuild the server:
npm run build
# or
pnpm buildInstallation
Installing via Smithery
To install Flux Schnell Image Generator for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @bytefer/mcp-flux-schnell --client claudeCursor Configuration
There are two ways to configure the MCP server in Cursor:
Project Configuration
For tools specific to a project, create a .cursor/mcp.json file in your project directory:
{
"mcpServers": {
"mcp-flux-schnell": {
"command": "node",
"args": ["/path/to/mcp-flux-schnell/build/index.js"],
"env": {
"FLUX_API_URL": "your flux api url",
"FLUX_API_TOKEN": "your flux api token",
"WORKING_DIR": "your working directory"
}
}
}
}This configuration will only be available within the specific project.
Global Configuration
For tools that you want to use across all projects, create a ~/.cursor/mcp.json file in your home directory with the same configuration:
{
"mcpServers": {
"mcp-flux-schnell": {
"command": "node",
"args": ["/path/to/mcp-flux-schnell/build/index.js"],
"env": {
"FLUX_API_URL": "your flux api url",
"FLUX_API_TOKEN": "your flux api token",
"WORKING_DIR": "your working directory"
}
}
}
}This makes the MCP server available in all your Cursor workspaces.
Available Tools
1 toolgenerate_imageC
Generate an image from a text prompt using Flux Schnell model
Inputs: prompt (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'generate_image' has a clear and distinct purpose that cannot be confused with any other tool in the set.
The single tool name 'generate_image' follows a clear verb_noun pattern. With only one tool, consistency is inherently perfect as there are no other names to compare against or deviate from.
A single tool is too few for most practical server purposes, as it severely limits functionality and flexibility. For an image generation server, typical expectations might include variations like upscaling, editing, or batch processing, making one tool feel thin and under-scoped.
The server's domain appears to be image generation, but with only a basic generation tool, there are significant gaps. Missing operations might include image editing, style variations, resolution adjustments, or batch processing, which could lead to agent failures when more complex tasks are required.
Maintenance
Related MCP Connectors
MCP server for Flux AI image generation
Generate AI images and videos from any compatible MCP client.
MCP server for OpenAI API (chat completions, image generation, embeddings) via AceDataCloud
MCP server for Qwen Image 3 AI image generation
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