How to Use the Adtelligent MCP in Google ADK

Q: How do I connect Google ADK to the Adtelligent MCP server?

Install the package with pip install google-adk. Initialize McpToolset using your Vinkius HTTP URL and attach it to your LlmAgent.

Q: What transport protocol does this MCP integration use?

The setup relies on StreamableHttpServerParameters for remote execution. Vinkius handles the connection layer so your Google Cloud infrastructure stays clean.

Feed Adtelligent MCP Server data directly into Google ADK for long-context Gemini reasoning.

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Connect Adtelligent MCP to Google ADK

Create your Vinkius account to connect Adtelligent 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 Adtelligent with Google ADK

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Analyze DSP campaigns alongside BigQuery data

Google ADK connects the `list_campaigns` tool straight to your Gemini agent. It pulls the active ad tech configurations and drops them into the reasoning pipeline. Cross-referencing these active flights with historical data in your Google Cloud environment happens instantly. The model matches current DSP spend against your internal user acquisition tables.

Expose Adtelligent MCP Server tools to Gemini

Running `list_advertisers` feeds massive arrays of demand-side partners into the context window. Gemini easily digests thousands of advertiser profiles without dropping details. You filter which functions the model sees using the `tool_names` parameter in `McpToolset`. This keeps the LLM focused strictly on advertiser discovery when building specific enterprise workflows.

Pull supply-side metrics into Vertex AI

Grabbing yield data requires executing `get_ssp_report` with your SSP Auth Token. The agent fetches the performance statistics and structures them for downstream processing. Enterprise setups often pipe this output directly into Vertex AI pipelines. It acts as the extraction layer, pulling raw ad tech numbers before passing them to specialized predictive models.

Setup guide

Set up Adtelligent 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 Adtelligent 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="Adtelligent_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Adtelligent tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Adtelligent. 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 Adtelligent MCP in Google ADK

Install the package with `pip install google-adk`. Initialize `McpToolset` using your Vinkius HTTP URL and attach it to your `LlmAgent`.

The framework allows explicit function filtering. Pass an array of allowed names to the toolset configuration to restrict access.

Grounding the model with real-time API responses prevents made-up identifiers. The agent reads the exact strings returned by the ad tech platform.

The setup relies on `StreamableHttpServerParameters` for remote execution. Vinkius handles the connection layer so your Google Cloud infrastructure stays clean.

Demand-side partner names and campaign budgets never leak across tenants. Every request executes inside a strict, isolated container that drops all state immediately after returning the payload.

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