SiliconFlow Flux MCP Server
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., "@SiliconFlow Flux MCP Server Generate an image of a peaceful garden with blooming flowers"
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.
SiliconFlow Flux MCP 服务器
这是一个基于Model Context Protocol (MCP)的服务器,允许AI通过MCP协议使用SiliconFlow的Flux模型进行图像生成。
功能特点
允许AI助手通过MCP协议调用SiliconFlow的Flux模型生成高质量图像
支持多种图像分辨率:1024x1024, 960x1280, 768x1024, 720x1440, 720x1280
可自定义生成参数,如随机种子等
缓存最近的图像生成结果
Related MCP server: Image Generation MCP Server
系统要求
Node.js v18.0.0 或更高版本
您可以通过以下命令验证Node.js安装:
node --version # 应显示v18.0.0或更高版本安装步骤
克隆仓库:
git clone https://github.com/lioensky/siliconflow-flux-mcp-server.git安装依赖:
npm install构建项目:
npm run build配置说明
API密钥配置
在使用前,您需要:
在项目根目录创建或编辑
.env文件通过https://cloud.siliconflow.cn/i/HxM1olJu 来获取14元额度密钥
添加您的SiliconFlow API密钥:
SILICONFLOW_API_KEY=您的API密钥注意:您需要自备SiliconFlow的API密钥才能使用此服务。
MCP服务器配置
在您的MCP配置文件中添加以下内容:
{
"mcpServers": {
"siliconflow-flux-mcp": {
"command": "node",
"args": ["路径/到/siliconflow-flux-mcp-server/build/index.js"],
"env": {
"SILICONFLOW_API_KEY": "您的API密钥"
}
}
}
}使用方法
配置完成后,AI助手可以通过MCP协议调用此服务生成图像。服务提供了generate_image工具,接受以下参数:
prompt:图像生成提示词(建议使用英文以获得最佳效果)resolution:图像分辨率,支持多种标准尺寸seed(可选):随机种子,用于生成可重复的结果
开发者工具
您可以使用MCP Inspector工具来测试服务器:
npm run inspector许可证
请参阅项目仓库中的许可证文件。
Available Tools
1 toolgenerate_imageA
Generates an image using the SiliconFlow API with the Flux Schnell model (black-forest-labs/FLUX.1-schnell). Provide a detailed English prompt and select a resolution. Nya~ <3 重要提示:
此工具返回一个基础的 HTML
<img>标签(包含 src 和 alt)。请在收到此标签后,为其添加一个
width属性,值应在 200 到 500 像素之间(例如width="300")。在最终回复用户时,请直接发送这个完整的、已添加
width属性的 HTML<img>标签,以便用户可以直接看到图片。
Inputs: prompt (required), resolution (required), seed.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
Only one tool exists, so there is no ambiguity between tools. The purpose is clearly to generate an image.
With a single tool, naming is trivially consistent. The name 'generate_image' follows a clear verb_noun pattern.
For a dedicated image generation server using a specific model, one tool is appropriate. It covers the core functionality without being too thin for its narrow scope.
The tool covers basic image generation but lacks advanced options like style or seed parameters. It is complete for a minimal server but has room for expansion.
Maintenance
Related MCP Connectors
Official FLUX MCP server. Generate, edit, vary, and browse images from Black Forest Labs.
Generate AI images, videos, music, SFX & speech in any AI assistant. Results appear inline in chat.
MCP server for Flux AI image generation
Image and video AI tools and your own pipelines, run from any AI assistant.
Related MCP Servers
- AlicenseBqualityBmaintenanceA Model Context Protocol server that enables high-quality image generation using the Flux.1 Schnell model via Together AI with customizable parameters.1304 npm10MIT
- AlicenseBqualityDmaintenanceA Model Context Protocol server that enables generation of high-quality images using the Flux.1 Schnell model via Together AI, allowing users to create images from text prompts with customizable dimensions.118MIT
- AlicenseNot gradedqualityNot gradedmaintenanceEnables high-quality image generation with advanced text rendering and contextual understanding using FLUX.1 Kontext Max through the Replicate API. Supports text-to-image generation, image editing, multiple aspect ratios, and automatically downloads generated images locally.1-
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to generate images using Cloudflare Workers AI models directly through the Model Context Protocol. It supports various models like Flux and Stable Diffusion, providing seamless image generation and storage via Cloudflare R2.7Apache 2.0