How to Use the Klevu (E-commerce AI Search) MCP in Cursor

Q: What tool do I use for custom sorting logic?

You use searchsorted to apply custom sort parameters to your search. This lets you verify that your UI handles price sorting, newest arrivals, or relevance rankings exactly as Klevu returns them.

Write storefront code using live Klevu (E-commerce AI Search) catalog data directly inside Cursor.

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Connect Klevu (E-commerce AI Search) MCP to Cursor

Create your Vinkius account to connect Klevu (E-commerce AI Search) to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Klevu (E-commerce AI Search) with Cursor

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Generate UI components using live search results

`search_keyword` fetches real-time product listings from your store's search index to feed directly into your active code files. Your Cursor agent calls this MCP tool to get real JSON payloads, allowing it to write accurate TypeScript interfaces and React components. No more writing components with mock data that fails in production. You get real payloads with actual image URLs, variant structures, and pricing fields to build storefront code.

Debug merchandising logic inside this Cursor MCP Server

`search_category` retrieves the exact product order for any collection page to let you verify smart merchandising rules directly in your editor. Your agent inspects the returned payload to ensure your frontend code maps the layout correctly. If you need to test custom sorting, `search_sorted` applies specific sort parameters to the keyword search. This lets you build and test sorting dropdowns with actual API responses.

Implement autocomplete and filters with real API responses

`search_autocomplete` generates live search suggestions as you mock user input using this MCP tool. You can build search bars that feel instant because you are writing the frontend logic against the actual autocomplete payload. Pair this with `search_filtered` to test how your UI handles facet selections like size or color. It eliminates the guesswork when mapping complex nested filter objects.

Setup guide

Set up Klevu (E-commerce AI Search) MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Klevu (E-commerce AI Search) MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Klevu (E-commerce AI Search) transactions." If the MCP tools are loaded correctly, Cursor will call the Klevu (E-commerce AI Search) tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "klevu-e-commerce-ai-search-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Klevu. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Klevu (E-commerce AI Search) MCP in Cursor

You ask the Cursor agent to search your catalog. It invokes `search_keyword` to pull live product data directly into your editor, which you can then use to generate or refactor your frontend code.

Yes. Ask your Cursor agent to test an autocomplete query, which triggers `search_autocomplete`. The agent uses the real JSON response to write or fix your search dropdown components.

You tell the agent to inspect a specific collection path. It calls `search_category` to retrieve the products and merchandising order, allowing you to debug layout issues in your editor.

You use `search_sorted` to apply custom sort parameters to your search. This lets you verify that your UI handles price sorting, newest arrivals, or relevance rankings exactly as Klevu returns them.

Your product catalog data and search queries are processed entirely inside the secure, ephemeral Vinkius sandbox using this MCP Server. Only the read-only product data required for search queries is fetched, leaving your master catalog write permissions completely untouched.

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