Tryonfy Mcp Server
@blasfin-finance
About Tryonfy Mcp Server
MCP server for TryOnfy - AI virtual try-on platform for clothes, hairstyles, and accessories
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"tryonfy": {
"command": "npx",
"args": [
"-y",
"tryonfy-mcp-server"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Tryonfy Mcp Server?
Tryonfy Mcp Server is a Model Context Protocol (MCP) server for TryOnfy, an AI-powered virtual try-on platform. It lets AI assistants interact with TryOnfy to preview clothing, hairstyles, and accessories instantly.
How to use Tryonfy Mcp Server?
Install the package globally with npm install -g tryonfy-mcp-server, then add it to your Claude Desktop configuration or run claude mcp add tryonfy -- npx -y tryonfy-mcp-server for Claude Code.
Key features of Tryonfy Mcp Server
- Lists all available virtual try-on features with descriptions
- Returns direct links for specific features like clothes or hairstyle changers
- Suggests the best feature based on natural language queries
- Provides current TryOnfy pricing information
Use cases of Tryonfy Mcp Server
- Query which virtual try-on features are available
- Get a direct link to a specific try-on tool (e.g., AI Clothes Changer)
- Ask for a feature recommendation by describing what you want to try
- Check TryOnfy’s pricing plans directly from a conversation
FAQ from Tryonfy Mcp Server
What does Tryonfy Mcp Server do?
It provides tools for AI assistants to interact with TryOnfy’s virtual try-on capabilities, such as listing features, getting links, suggesting features, and viewing pricing.
How do I install Tryonfy Mcp Server?
Install it globally via npm: npm install -g tryonfy-mcp-server.
How do I use Tryonfy Mcp Server with Claude Desktop?
Add the server to your Claude Desktop config (claude_desktop_config.json) with the command npx -y tryonfy-mcp-server.
What tools does Tryonfy Mcp Server provide?
It provides four tools: list_features, get_tryon_link, suggest_feature, and get_pricing.
How do I get a feature recommendation from Tryonfy Mcp Server?
Use the suggest_feature tool with a natural language query, for example “I want to try a new hairstyle” to get the AI Hairstyle Changer.
Frequently asked questions
What does Tryonfy Mcp Server do?
It provides tools for AI assistants to interact with TryOnfy’s virtual try-on capabilities, such as listing features, getting links, suggesting features, and viewing pricing.
How do I install Tryonfy Mcp Server?
Install it globally via npm: `npm install -g tryonfy-mcp-server`.
How do I use Tryonfy Mcp Server with Claude Desktop?
Add the server to your Claude Desktop config (`claude_desktop_config.json`) with the command `npx -y tryonfy-mcp-server`.
What tools does Tryonfy Mcp Server provide?
It provides four tools: `list_features`, `get_tryon_link`, `suggest_feature`, and `get_pricing`.
How do I get a feature recommendation from Tryonfy Mcp Server?
Use the `suggest_feature` tool with a natural language query, for example “I want to try a new hairstyle” to get the AI Hairstyle Changer.
Basic information
More Other MCP servers
🚀 Model Context Protocol (MCP) Curriculum for Beginners
microsoftThis open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
Website
FunnyWolfAdversary simulation and Red teaming platform with AI
Mobile Mcp
mobile-nextModel Context Protocol Server for Mobile Automation and Scraping (iOS, Android, Emulators, Simulators and Real Devices)
Sequential Thinking
modelcontextprotocolModel Context Protocol Servers
Peekaboo MCP – lightning-fast macOS screenshots for AI agents
steipetePeekaboo is a macOS CLI & optional MCP server that enables AI agents to capture screenshots of applications, or the entire system, with optional visual question answering through local or remote AI models.
Comments