How to Use the Akeneo PIM MCP in Google ADK

Q: How do I configure Google ADK to use the Akeneo PIM MCP Server?

Install the google-adk package and set up an McpToolset using your Vinkius HTTP endpoint. Pass this toolset into your LlmAgent configuration to expose the tools to Gemini.

Q: Can I restrict which Akeneo PIM tools are exposed to Google ADK?

Yes, you can use the optional toolnames filter when initializing the toolset. This restricts the MCP server to read-only tools like listproducts if you want to block write operations like updateproduct.

Connect your Akeneo PIM catalog to Google ADK to analyze and update millions of products using Gemini long-context reasoning.

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Setup Akeneo PIM with Google ADK

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Analyze entire catalogs with Gemini

Feed your entire product catalog directly into Gemini's massive context window. By calling `list_products` and `list_categories`, your agent pulls thousands of items into a single reasoning step to find inconsistencies. This setup bypasses the need for complex search indexing. The agent reads raw category trees and processes them alongside your BigQuery sales data to flag underperforming products.

Enterprise PIM updates via Google ADK

Keep your PIM synchronized with your Google Cloud data pipelines. The agent uses `list_channels` and `get_attribute_details` to check which attributes are required for your mobile or web storefronts. Once the agent identifies gaps, it executes targeted updates using `update_product`. This automation ensures your Google Merchant Center feeds match your PIM data perfectly, all driven by native MCP tools.

Automated family and attribute mapping

Organize messy supplier spreadsheets into clean PIM structures. Your agent calls `list_families` and `list_attributes` to understand your existing schema before placing new inventory. It checks the details of each category with `get_category_details` to ensure accurate placement. This eliminates manual data entry when onboarding new product lines.

Setup guide

Set up Akeneo PIM MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Akeneo PIM tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Akeneo PIM_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Akeneo PIM tools via MCP.",
    tools=mcp_tools,
)

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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 Google ADK

Install the `google-adk` package and set up an `McpToolset` using your Vinkius HTTP endpoint. Pass this toolset into your `LlmAgent` configuration to expose the tools to Gemini.

Yes, you can use the optional `tool_names` filter when initializing the toolset. This restricts the MCP server to read-only tools like `list_products` if you want to block write operations like `update_product`.

Gemini models handle over one million tokens, letting the agent ingest deep attribute lists from `list_attributes` without running out of memory. This allows for deep reasoning across your entire taxonomy.

Yes, your agent can query sales trends from BigQuery, then use `get_product_details` to check the current PIM setup, and finally run `update_product` to adjust tags based on performance.

Your product families, attribute metadata, and category trees are processed in memory within your Google Cloud boundary. Vinkius secures the MCP server endpoint with zero-trust token authentication to prevent unauthorized catalog access.

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