Ali-Flux MCP Server

@echozyr2001

Basic information

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.

Ali-Flux MCP Server 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

Ali-Flux MCP Server 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

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.

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