How to Use the DoiT MCP in Google ADK

Q: How does Google ADK interact with the multi-cloud features of DoiT?

The agent uses listconnectedcloudaccounts to gather all linked AWS, GCP, and Azure accounts. It then uses this list to query individual asset details across cloud boundaries.

Q: How do I get a quick summary of our total spend?

Your agent invokes getbillingcostsummary to retrieve a high-level overview of your total cloud expenditure. It provides a clean breakdown of costs without requiring manual API calls.

Give your Gemini agents on Google ADK direct access to multi-cloud cost data with this DoiT MCP Server.

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Connect DoiT MCP to Google ADK

Create your Vinkius account to connect DoiT 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 DoiT with Google ADK

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Monitor cost anomalies using Google ADK

This MCP Server provides `list_cost_anomalies` to let your Gemini agent detect unexpected spending trends across your cloud deployments. It connects your long-context model directly to real-time anomaly feeds. Your agent parses these anomalies alongside your BigQuery datasets to correlate traffic spikes with cost increases. It helps you find out exactly why your GCP or AWS bill jumped overnight.

Audit cloud resources via Google ADK

The `list_cloud_assets` tool lists every single managed cloud resource across AWS, GCP, and Azure. It feeds your agent a complete inventory of your infrastructure in seconds. Your agent uses this inventory to cross-reference active resources with your internal databases. You can easily find abandoned VMs or untagged databases that are wasting money.

Track exceeded budgets with Google ADK

The `list_cost_budgets` tool retrieves all configured budgets from your account. It allows your agent to keep a constant watch on your infrastructure spending limits. When a budget is breached, the agent calls `list_exceeded_cost_budgets` to identify the exact thresholds crossed. Your Gemini agent can then write a detailed summary of the breach directly to your team's chat.

Setup guide

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

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Common questions about DoiT MCP in Google ADK

Install the SDK, then define a toolset pointing to the Vinkius MCP server HTTP URL. Pass this toolset into your agent constructor to expose all ten cost-tracking tools to Gemini.

Yes, you can pass a list of allowed tool names to your toolset configuration. This prevents your agent from calling sensitive tools like `list_critical_cost_spikes` if you only want it to read basic summaries.

The agent uses `list_connected_cloud_accounts` to gather all linked AWS, GCP, and Azure accounts. It then uses this list to query individual asset details across cloud boundaries.

Your agent invokes `get_billing_cost_summary` to retrieve a high-level overview of your total cloud expenditure. It provides a clean breakdown of costs without requiring manual API calls.

All MCP queries pass through secure, ephemeral V8 isolates managed by Vinkius. Your cloud cost and asset metadata is never cached, keeping your corporate billing records completely private.

Use it with your favorite AI tools

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