How to Use the Criteo Marketing API MCP in Google ADK

Q: How do I link Criteo Marketing API to Google ADK?

Use the McpToolset class with your server URL to create a toolset. Once you pass this to the LlmAgent, your agent gains immediate access to the full Criteo tool suite.

Connect Google ADK to your Criteo Marketing API. Enterprise-ready marketing intelligence on Google Cloud infrastructure.

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Connect Criteo Marketing API MCP to Google ADK

Create your Vinkius account to connect Criteo Marketing API to Google ADK 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 Criteo Marketing API with Google ADK

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Analyze performance in Google ADK

Your agent uses `get_marketing_statistics` to pull data directly into your Google Cloud agent logic. It processes large datasets to find trends in your campaign spend. By leveraging `list_marketing_campaigns`, the agent creates a clear view of your active account status. It provides long-context reasoning over your entire marketing history.

Manage ad sets via Google ADK

The agent reads specific configurations using `get_ad_set_details` while checking active groups via `list_ad_sets`. It connects your infrastructure directly to your Criteo settings. This MCP server ensures your agent can query the API to compare budget allocations. It keeps your marketing data synchronized with your BigQuery workloads.

Targeting and creative visibility

Your agent lists available segments using `list_audience_segments` to refine your campaign logic. It keeps your targeting strategy updated based on real-time API feedback. It also scans `list_ad_creatives` to audit your current assets. Your Google ADK agent now understands exactly which content is live for every audience.

Setup guide

Set up Criteo Marketing API 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 Criteo Marketing API 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="Criteo Marketing API_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Criteo Marketing API 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 Criteo Marketing. 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 Criteo Marketing API MCP in Google ADK

Use the `McpToolset` class with your server URL to create a toolset. Once you pass this to the `LlmAgent`, your agent gains immediate access to the full Criteo tool suite.

It is, and you can easily restrict which tools the agent uses by applying a `tool_names` filter. This keeps your Google Cloud environment clean and focused on specific marketing tasks.

Gemini models used in this framework support massive context windows. You can feed entire campaign lists and detailed statistics back into the agent for deep analysis.

The server supports both Stdio and HTTP, giving you flexibility in how your agent communicates. You can choose the transport that fits your existing Google Cloud architecture.

We enforce strict zero-trust principles for all data transmission. Your audience segments and campaign IDs are processed in an ephemeral sandbox, meaning no personal or proprietary data persists once your agent session terminates.

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