Ali-Flux MCP Server

@echozyr2001

About Ali-Flux MCP Server

A simple MCP server for generating images using Ali Cloud's DashScope API, with tools for task management and local image saving.

Config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Tools

Generate images using Alibaba Cloud DashScope API

Check image generation task status

Download generated images and save them locally

Overview

What is Ali-Flux MCP Server?

It is a TypeScript-based Model Context Protocol server that integrates with Alibaba Cloud DashScope API to generate images and save them locally. It is intended for developers using MCP-compatible clients (e.g., Claude Desktop) who need AI image generation capabilities.

How to use Ali-Flux MCP Server?

Install dependencies with npm install, build the server with npm run build, and set the required environment variables (DASHSCOPE_API_KEY, optionally SAVE_DIR, MODEL_NAME, WORK_DIR). Then configure your MCP client (e.g., Claude Desktop) using the command and env fields as shown in the README.

Key features of Ali-Flux MCP Server

Provides three tools: generate_image, check_task_status, and download_image
Generates images via Alibaba Cloud DashScope API using text prompts
Supports optional image parameters: size, seed, and steps
Checks task status and downloads generated images to local storage
Configurable save directory and model name via environment variables

Use cases of Ali-Flux MCP Server

Generate images from text prompts directly within Claude Desktop
Automate image creation pipelines with task status polling
Save generated images to a custom local folder for later use
Integrate Alibaba Cloud image generation into personal or business workflows

FAQ from Ali-Flux MCP Server

What tools does Ali-Flux MCP Server provide?

It offers generate_image (submit a prompt and optional parameters), check_task_status (poll for task completion), and download_image (save generated images to a local directory).

What environment variables are required?

You must set DASHSCOPE_API_KEY. Optional variables include SAVE_DIR (default: ~/Desktop/flux-images), MODEL_NAME (default: flux-merged), and WORK_DIR (default: current working directory).

How do I debug the server?

Since MCP servers communicate over stdio, use the built-in script npm run inspector which launches the MCP Inspector for debugging.

What image parameters can I customize?

When calling generate_image, you can specify size, seed, and steps in addition to the required prompt.

How are generated images saved?

The download_image tool saves all images from a completed task to the directory specified by SAVE_DIR or a custom save_path (must be absolute). A base_dir can be used for resolving relative paths.

Frequently asked questions

What tools does Ali-Flux MCP Server provide?

It offers `generate_image` (submit a prompt and optional parameters), `check_task_status` (poll for task completion), and `download_image` (save generated images to a local directory).

What environment variables are required?

You must set `DASHSCOPE_API_KEY`. Optional variables include `SAVE_DIR` (default: `~/Desktop/flux-images`), `MODEL_NAME` (default: `flux-merged`), and `WORK_DIR` (default: current working directory).

How do I debug the server?

Since MCP servers communicate over stdio, use the built-in script `npm run inspector` which launches the MCP Inspector for debugging.

What image parameters can I customize?

When calling `generate_image`, you can specify `size`, `seed`, and `steps` in addition to the required `prompt`.

How are generated images saved?

The `download_image` tool saves all images from a completed task to the directory specified by `SAVE_DIR` or a custom `save_path` (must be absolute). A `base_dir` can be used for resolving relative paths.