How to Use the Expensya MCP in Google ADK

Q: Can I restrict which Expensya tools my Google ADK agent uses?

You can use a toolnames filter during initialization. This limits the agent to only the specific actions you want to permit.

Q: Can I use Expensya to export data to BigQuery via Google ADK?

Yes, you can trigger exportexpensedata and pipe the output into your BigQuery tables. It works as part of your standard data ingestion loop.

Connect Expensya to your Google ADK agent. Build enterprise-grade financial workflows on top of Google Cloud infrastructure.

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Connect Expensya MCP to Google ADK

Create your Vinkius account to connect Expensya 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 Expensya with Google ADK

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Sync expenses with Google ADK

Your agent uses `list_expense_reports` to pull current data into your Google Cloud environment. It allows for long-context reasoning over your entire financial history. This is ideal if you need to reconcile thousands of entries at once. The agent parses the data and flags anomalies against your defined categories.

Categorize spending automatically

Your agent calls `list_expense_categories` to ensure every submission is tagged correctly. It maintains consistency across your entire organization. It prevents misclassification errors that usually plague manual expense tracking. The agent enforces these tags whenever a user submits a new receipt.

Track project budgets

Use `list_analytical_projects` to map expenses directly to internal initiatives. The agent tracks burn rates in real-time as new records hit the server. It gives your finance team a live dashboard of project costs. You stop waiting for end-of-month reports to see where the money is going.

Setup guide

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

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Common questions about Expensya MCP in Google ADK

You initialize an McpToolset with the server URL and include it in your agent definition. It connects directly to your existing Google Cloud setup.

You can use a tool_names filter during initialization. This limits the agent to only the specific actions you want to permit.

Absolutely. Your agent can ingest massive amounts of data from `list_expenses` and hold that context to perform complex financial analysis.

All traffic is handled through an ephemeral Vinkius sandbox. Your sensitive receipt data and user profiles are never cached or exposed to other agents.

Yes, you can trigger `export_expense_data` and pipe the output into your BigQuery tables. It works as part of your standard data ingestion loop.

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