MODEL CONTEXT PROTOCOL
Virtual try-on, inside your AI assistant.
Genlook ships a remote MCP server that turns the Virtual Try-On API into tools your AI assistant can call: upload a photo, generate a try-on, and view the result in the conversation. OAuth means no API keys, and new accounts start with 5 free credits.
Add Genlook to any MCP-compatible assistant and try clothes on in plain language. The server lives at:
https://mcp.genlook.app
No API key needed. The connector authenticates with OAuth. Sign in (or create an account) when your assistant prompts you, and you're ready to generate.
5
Free credits to start, no card required.
1 credit
Per try-on generation.
OAuth
No API keys to copy, paste, or rotate.
~10s
From prompt to on-body result in the chat.
01 · Connect
Three steps, no keys.
Add the connector
Point your assistant at https://mcp.genlook.app as a custom MCP / HTTP connector.
Sign in with OAuth
Approve access with your Genlook account, no keys to manage or rotate.
Start generating
Ask your assistant to try a garment on a photo, and the result appears right in the chat.
Set it up in your client
Claude
- Open claude.ai → Settings → Connectors
- Click Add custom connector and paste
https://mcp.genlook.app - Sign in with your Genlook account when prompted
Claude Code
claude mcp add --transport http genlook https://mcp.genlook.app
Then run /mcp inside Claude Code to complete the OAuth sign-in.
ChatGPT
- Settings → Apps & Connectors → enable Developer mode
- Create a connector with
https://mcp.genlook.app(OAuth) - Sign in with your Genlook account when prompted
Cursor
Add to ~/.cursor/mcp.json (or via Settings → MCP → Add new MCP server):
{
"mcpServers": {
"genlook": {
"url": "https://mcp.genlook.app"
}
}
}
Cursor handles the OAuth flow on first use.
Tools
The tools mirror the REST API:
| Tool | What it does |
|---|---|
upload_photo | Upload a person photo (public URL or base64). Returns an imageId to reuse for try-ons. |
get_uploaded_photo | Return your most recent non-expired upload so you don't have to re-upload between conversations. |
generate_try_on | Generate a try-on from a garment image URL on a given person photo. Waits and returns the result. |
get_generation | Poll a generation by id; returns the image once it's complete. |
get_account | Show remaining credits and the top-up URL. |
All image URLs passed to the tools must be publicly accessible, no login-gated or private links.
Example prompts
- "Here's a dress I like: <image URL>, show me wearing it."
- "Use this photo of me from now on: <image URL>."
- "Try these sneakers on me, then compare with the previous pair."
- "How many try-on credits do I have left?"
The same engine that powers the Genlook storefront widget runs behind the MCP tools. A single photo plus a garment URL is enough to get a clean, on-body result back in the conversation. Uploaded photos and generated images follow the account retention window (7 days by default), then are deleted automatically.
Building for a storefront instead?
Try-On API for developers →Shopify app →WooCommerce plugin →Same engine, same account
02 · MCP, specifically
Asked before connecting.
Do I need an API key?↓
No. The MCP connector uses OAuth. Sign in with your Genlook account and you're authenticated. There are no keys to copy or rotate.
How much does it cost?↓
New accounts start with 5 free credits, and each generation costs 1 credit. Top up anytime at platform.genlook.app/topup.
Which clients work?↓
Any MCP-compatible client over Streamable HTTP, including Claude, Claude Code, ChatGPT (developer mode), and Cursor.
Is it the same engine as the storefront widget?↓
Yes. The MCP tools call the same Virtual Try-On API and the same Account and credits as platform.genlook.app.
Try it on from your AI assistant.
Connect the MCP server and start with 5 free credits, top up anytime.