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

Q: What happens if I need to run a custom API payload?

You use searchraw to send custom JSON payloads directly to the Klevu API. This lets you test advanced query configurations that aren't covered by the standard tool parameters.

Search your store's live catalog and test product recommendations directly inside Claude Desktop.

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Connect Klevu (E-commerce AI Search) MCP to Claude Desktop

Create your Vinkius account to connect Klevu (E-commerce AI Search) to Claude Desktop 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 Claude Desktop

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Query your live catalog with natural language

`search_keyword` queries your storefront catalog using Klevu's AI search engine to retrieve matched products instantly. You type a conversational search query in Claude Desktop, and your agent returns accurate product matches with pricing, image URLs, and stock levels. This MCP tool bypasses the typical manual API testing tools. You can also use `search_product_id` to grab raw details for a single SKU when debugging catalog sync issues.

Build and test category pages inside this MCP Server

`search_category` pulls products assigned to specific collection paths to let you verify smart category merchandising rules on the fly. Your AI client pulls the exact product order and pricing rules that your shoppers see on the live storefront. You can chain this with `search_filtered` to apply facet filters like color, size, or brand. It lets you debug complex navigation paths without writing frontend test code.

Preview real-time trending products and recommendations

`search_trending` retrieves the top-performing products across your entire store based on real shopper behavior. Ask Claude Desktop what is selling right now, and the MCP Server returns the exact list of trending items. Switch to `search_recs` to fetch personalized product recommendations for specific items or shopper profiles. It makes verifying recommendation logic as simple as having a quick conversation with your agent.

Setup guide

Set up Klevu (E-commerce AI Search) MCP in Claude Web or Desktop

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.
2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.
3

Start a conversation

Open a new chat. The Klevu (E-commerce AI Search) MCP tools are available immediately — no restart needed.

Endpoint URL

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

No configuration file needed — paste the URL directly in the Claude web interface.

Available on Free (1 connector), Pro, Max, Team, and Enterprise plans.

Prerequisites

Claude Desktop installed (macOS or Windows)
Active Vinkius subscription with a valid endpoint token

1

Open Claude Desktop Settings

Click the menu icon at the top-left corner, go to Settings → Developer → Edit Config. This opens claude_desktop_config.json in your default text editor.
2

Paste the Klevu (E-commerce AI Search) MCP configuration

Copy the JSON snippet on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Desktop

Close and reopen the application. Claude needs a full restart to load new MCPs — refreshing a conversation is not enough.
4

Verify the connection

Open a new conversation. Click the 🔌 icon at the bottom of the message input. You should see tools listed under klevu-e-commerce-ai-search-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 Claude Desktop

You ask Claude Desktop to search for a product or category. The model automatically chooses `search_keyword` or `search_category` to fetch live data from your Klevu index and displays the results in your chat window.

Yes. You tell your agent to filter by attributes like brand, size, or color, and it calls `search_filtered` with those parameters. You get back the exact subset of products matching those constraints.

Tell Claude Desktop to load a specific collection path. The agent invokes `search_category` to retrieve the products and merchandising order, allowing you to debug layout issues in your chat window.

You use `search_raw` to send custom JSON payloads directly to the Klevu API. This lets you test advanced query configurations that aren't covered by the standard tool parameters.

Your store's catalog data remains completely secure when using this MCP Server. This server only handles read-only search queries, product IDs, and category paths. No customer personal data or payment details ever pass through the Vinkius sandbox, keeping your catalog access secure.

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