Vybe Virtual Try-On MCP Server

Vybe Virtual Try-On MCP Server

A FastMCP server that provides virtual try-on functionality through the Replicate API, allowing users to visualize how clothing items would look on models.

Category
访问服务器

README

Vybe Virtual Try-On MCP Server

A FastMCP server that wraps the Replicate API for virtual try-on functionality, ready for deployment to Render.

Setup

Using UV (recommended)

  1. Install uv if you haven't already:
curl -LsSf https://astral.sh/uv/install.sh | sh
  1. Install dependencies:
uv sync
  1. Set up environment variables:
cp .env.example .env

Edit .env and add your Replicate API token.

Using pip (alternative)

  1. Install dependencies:
pip install -r requirements.txt
  1. Set up environment variables:
cp .env.example .env

Edit .env and add your Replicate API token.

Local Testing

Run the server locally:

# With uv (recommended)
uv run python server.py

# Or with regular python
python server.py

The server will start on the default FastMCP port and expose the virtual_tryon tool.

MCP Client Configuration

Add to your Claude Desktop or other MCP client configuration:

{
  "mcpServers": {
    "vybe-virtual-tryon": {
      "command": "python",
      "args": ["/path/to/server.py"]
    }
  }
}

Usage

The server exposes three tools:

test_connection

Tests the connection and shows timeout configuration.

base64_to_url

Converts base64 encoded images to data URIs for use with virtual_tryon:

  • base64_image: Base64 encoded image string (with or without data:image prefix)
  • image_type: Image type (png, jpg, jpeg, gif, webp) - default: png

Returns a data URI that can be used as model_image or garment_image in virtual_tryon.

virtual_tryon

Performs virtual try-on with these parameters:

  • model_image: URL or data URI of the person/model image
  • garment_image: URL or data URI of the clothing item to try on
  • Various optional parameters for customization

Timeout Configuration

The server is configured with extended timeouts to handle long-running Replicate operations:

  • MCP request timeout: 600 seconds (10 minutes)
  • Replicate polling interval: 5 seconds
  • Replicate timeout: 600 seconds (10 minutes)

If you still experience timeouts, you can adjust these in the server.py file.

Deployment to Render

Quick Deploy with render.yaml

  1. Push your code to a GitHub repository
  2. Connect the repository to Render
  3. Render will automatically detect the render.yaml configuration
  4. Add your REPLICATE_API_TOKEN in the Render dashboard under Environment Variables
  5. Deploy!

The service includes health check endpoints:

  • /health - Health check endpoint for Render monitoring
  • / - Root endpoint with service status

Manual Setup

If you prefer manual configuration:

  1. Create a new Web Service on Render
  2. Connect your GitHub repository
  3. Configure the service:
    • Build Command: curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.cargo/env && uv sync --frozen --no-dev
    • Start Command: uv run python server.py
    • Health Check Path: /health
  4. Add environment variables:
    • REPLICATE_API_TOKEN: Your Replicate API token (required)
    • PORT: (leave empty, Render will auto-assign)
    • HOST: (leave empty, defaults to 0.0.0.0)

Using the Remote MCP Server

Once deployed, you can access the server at:

  • Health Check: https://your-service-name.onrender.com/health
  • Root: https://your-service-name.onrender.com/
  • MCP Protocol: Use the base URL for MCP client connections

For MCP clients that support HTTP transport:

{
  "mcpServers": {
    "vybe-virtual-tryon-remote": {
      "url": "https://your-service-name.onrender.com",
      "transport": "http"
    }
  }
}

Replace your-service-name with your actual Render service URL.

Testing the Deployment

Use the included test script to verify your deployment is working:

# With uv (if using uv environment)
uv run python test_deployment.py https://your-service-name.onrender.com

# Or with regular python
python test_deployment.py https://your-service-name.onrender.com

This will test:

  • Health check endpoint (/health)
  • Root endpoint (/)
  • Basic MCP server connectivity

Example output:

Testing deployment at: https://your-service.onrender.com
--------------------------------------------------

🧪 Testing Health Endpoint...
✅ Health check passed: {'status': 'healthy', 'service': 'vybe-virtual-tryon'}

🧪 Testing Root Endpoint...
✅ Root endpoint passed: {'message': 'Vybe Virtual Try-On MCP Server', 'status': 'running'}

🧪 Testing MCP Connection...
✅ MCP server is responding

==================================================
TEST RESULTS:
==================================================
✅ PASS - Health Endpoint
✅ PASS - Root Endpoint
✅ PASS - MCP Connection

Tests passed: 3/3

🎉 All tests passed! Deployment is working correctly.

Docker Deployment (Alternative)

A Dockerfile is also included if you prefer containerized deployment. Render will automatically detect and use it if present.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选