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

Q: How do I sort search results dynamically using these tools?

You use the searchsorted tool. This allows your agent to specify custom sorting parameters, such as price or popularity, directly in the workflow arguments based on what the shopper asked for.

Build resilient e-commerce workflows with Mastra AI and automated Klevu search tools.

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

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

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Bulletproof search workflows with Mastra AI

E-commerce APIs can sometimes fail during high-traffic sales. Mastra AI lets you wrap tools like `search_keyword` and `search_sorted` in resilient workflows using this MCP Server to handle API errors and automatically retry with exponential backoff if a network hiccup occurs. You can set up conditional paths directly in code. For example, if a search returns zero results, your agent can automatically trigger `search_trending` to show fallback products instead of an empty screen.

Automated merchandising via MCP Server integration

Manage your category pages programmatically without manual intervention. By combining `search_category` with Mastra's workflow engine, you can build agents that audit your storefront navigation daily to ensure high-margin items are displayed first. The agent uses `search_filtered` to check product availability across different sizes and colors. If stock levels drop, the workflow can automatically trigger an alert or update the category layout on the fly.

Smart recommendations with human-in-the-loop approval

Sometimes you want to review what recommendations are being generated before they go live on a major landing page. Mastra AI supports human-in-the-loop validation for tools like `search_recs`. The workflow pauses and requests approval from an admin. Once approved, the agent pushes the updated product recommendations to your storefront, giving you perfect control over your brand's presentation.

Setup guide

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

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Klevu (E-commerce AI Search) tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "klevu-e-commerce-ai-search-mcp-client",
  servers: {
    "klevu-e-commerce-ai-search-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Klevu (E-commerce AI Search) Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Klevu (E-commerce AI Search) tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Klevu (E-commerce AI Search) transactions"
);
console.log(result.text);

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

Mastra AI's built-in workflow engine lets you define retry policies for tools like `search_keyword`. If the API rate limits your request, the agent will back off and retry automatically.

Yes, you can chain tools sequentially. For instance, your agent can call `search_autocomplete` to find matching categories, then immediately call `search_category` to pull the actual products for those categories.

Mastra agents deploy to any cloud provider with a single command. You only need to pass your Vinkius MCP endpoint token as an environment variable to give your deployed agent secure access to the search tools.

You use the `search_sorted` tool. This allows your agent to specify custom sorting parameters, such as price or popularity, directly in the workflow arguments based on what the shopper asked for.

Every request containing search queries and product IDs is isolated in a zero-trust, ephemeral V8 container. The data is processed in-memory to execute the search and is immediately destroyed once the payload is returned.

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