How to Use the AdButler MCP in Google ADK

Q: How do I configure the AdButler MCP Server inside a Google ADK agent?

Install google-adk and define your McpToolset using the Vinkius HTTP transport parameters. Pass this toolset into your LlmAgent constructor to give Gemini access to your ad data.

Q: How does Google ADK handle large lists of AdButler banners?

The SDK passes the output of listbanners directly into Gemini's long-context window. The model can process thousands of banner records and campaign configurations without running out of memory.

Q: Can I restrict my Google Cloud agent to read-only AdButler MCP tools?

Yes. Use the toolnames filter in the McpToolset setup to only expose tools like listcampaigns and getcampaign, hiding any modification tools.

Q: Where is my AdButler campaign data processed when using Google ADK?

Data retrieved via getcampaign and listcampaigns is processed within secure, ephemeral V8 isolates. Vinkius handles the underlying API authentication, ensuring your AdButler campaign budgets and advertiser names are never stored or logged during Google ADK executions.

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Connect AdButler MCP to Google ADK

Create your Vinkius account to connect AdButler 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 AdButler with Google ADK

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Map AdButler Placements to BigQuery Data

The `list_placements` tool pulls active ad placements directly into your Google ADK agent's reasoning window. This connects your live inventory with historical performance data stored in BigQuery. By combining `list_zones` with your BigQuery data warehouse, the Google ADK agent identifies empty inventory. The MCP Server provides the raw endpoint data, and Gemini's million-token context processes your entire publisher list in a single turn.

Analyze Advertiser Performance at Scale

The `get_stats` tool pulls impression and click metrics directly for your Google ADK agent. Your agent uses this data to calculate click-through rates without manual reporting. You can filter tools using the `tool_names` parameter in your Google ADK `McpToolset` configuration to expose only `get_advertiser` and `list_banners` from the MCP Server. This keeps your agent focused on advertiser-specific tasks without exposing administrative tools.

Audit Publisher Inventories via Google ADK

The `list_publishers` tool gives your Google ADK agent a complete view of your external publishing partners and their assigned zones. Your agent matches these partners against your internal Google Cloud databases to find billing discrepancies. Running `check_adbutler_status` inside your Google ADK agent workflow confirms API availability before initiating large-scale publisher audits. This prevents API timeouts from interrupting your automated data pipelines.

Setup guide

Set up AdButler 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 AdButler 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="AdButler_agent",
    model="gemini-2.0-flash",
    instruction="You have access to AdButler 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 AdButler. 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 AdButler MCP in Google ADK

Install `google-adk` and define your `McpToolset` using the Vinkius HTTP transport parameters. Pass this toolset into your `LlmAgent` constructor to give Gemini access to your ad data.

Yes. Your agent can read historical performance from BigQuery and then use `get_stats` to compare those numbers with live ad serving metrics in real time.

The SDK passes the output of `list_banners` directly into Gemini's long-context window. The model can process thousands of banner records and campaign configurations without running out of memory.

Yes. Use the `tool_names` filter in the `McpToolset` setup to only expose tools like `list_campaigns` and `get_campaign`, hiding any modification tools.

Data retrieved via `get_campaign` and `list_campaigns` is processed within secure, ephemeral V8 isolates. Vinkius handles the underlying API authentication, ensuring your AdButler campaign budgets and advertiser names are never stored or logged during Google ADK executions.

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