How to Use the Akeneo PIM MCP in Mastra AI

Q: Is it possible to filter products in Akeneo PIM using Mastra AI?

You use the listproducts tool which supports pagination. You can feed those results into your agent's memory to filter by attributes or categories.

Build complex product management workflows in Mastra AI using this MCP Server for reliable, automated catalog operations.

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Connect Akeneo PIM MCP to Mastra AI

Create your Vinkius account to connect Akeneo PIM 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 Akeneo PIM with Mastra AI

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Automate catalog edits with Mastra AI

Chain `list_products` and `update_product` inside your Mastra agents to handle bulk catalog maintenance. Define your logic in the workflow engine, and let the agent perform the heavy lifting on your PIM records. If a product update fails, the agent uses Mastra's built-in retry logic to attempt the operation again. It prevents data drift by ensuring your PIM stays in sync with your external sources.

Conditional product routing

Use `get_category_details` to branch your workflow based on specific product classifications. Your agent evaluates the data and decides whether to send updates to specific channels or flag them for manual review. This approach lets you build complex logic where `list_families` acts as a trigger for different processing paths. It keeps your operations clean and avoids hard-coded scripts that break when your catalog changes.

Reliable PIM monitoring

Connect your Mastra workflows to the PIM using `list_locales` to monitor availability across regions. Your agents check for missing translations and trigger alerts if your product data doesn't meet regional requirements. By delegating these checks to an agent, you stop wasting time on manual audits. The workflow engine handles the execution, and the server provides the raw data needed to make informed decisions.

Setup guide

Set up Akeneo PIM 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 Akeneo PIM 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: "akeneo-pim-mcp-client",
  servers: {
    "akeneo-pim-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent Akeneo PIM transactions"
);
console.log(result.text);

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Akeneo PIM. 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 Akeneo PIM MCP in Mastra AI

Add the server URL to your Mastra client configuration. Once defined, you can call any tool like `get_product_details` directly within your agent steps.

Yes, Mastra's native workflow engine manages retries and conditional branching. You can define specific logic to handle cases where `update_product` might fail.

You use the `list_products` tool which supports pagination. You can feed those results into your agent's memory to filter by attributes or categories.

You can enable tool approval in your Mastra agent definition. This forces the agent to pause before executing critical actions like `update_product`.

All requests are encrypted in transit and handled through a secure, isolated sandbox. Your product metadata never persists beyond the execution of your agent workflow.

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