How to Use the Wise MCP in Google ADK

Q: Can I use Wise data from the Google ADK for my enterprise agents?

Yes. You can pull structured data, such as liststatements or full transfer history (listtransfers), and load that into BigQuery to train your models.

Q: What financial actions are possible using Wise with the Google ADK?

The agent can handle quoting, checking rates via getexchangerate, and listing recipients. It covers both real-time data retrieval and historical record keeping through this MCP Server.

Q: Is tracking multi-currency balances reliable with the Google ADK?

It is. The tool listbalances provides a comprehensive snapshot, giving you immediate visibility into all your accounts simultaneously within your enterprise workflow.

Act on global money movements using the Google ADK for enterprise scale.

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Connect Wise MCP to Google ADK

Create your Vinkius account to connect Wise 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 Wise with Google ADK

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Analyze Finances Across BigQuery with MCP Server

Because you're building enterprise agents, you need context. The agent can pull live multi-currency data via `list_balances` and feed it directly into your existing BigQuery tables. It’s ideal for massive dataset analysis. You don't just get a balance; you get the raw numbers to reason over in Vertex AI.

Streamline Transfer Logic with Google ADK

The agent doesn't just check rates; it builds full, multi-step financial pipelines. It first checks `get_exchange_rate` and then uses that to structure a quote via `create_quote`. This sequence runs automatically. The result is an action plan for your agents: getting the necessary transfer details using `get_transfer` before committing.

Manage Wise Profiles Using Google ADK

The agent keeps track of all business entities and contacts. It lists available profiles with `list_profiles`, which is critical when managing multiple legal structures. It also helps manage who gets paid by listing payment recipients via `list_recipients`. This structured approach ensures your agents always know who they're dealing with.

Setup guide

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

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Common questions about Wise MCP in Google ADK

The MCP Server allows your agent to execute financial tools like `list_balances` directly within your Google Cloud environment. This means you can trigger actions and then analyze the results using long-context reasoning in Gemini.

Yes. You can pull structured data, such as `list_statements` or full transfer history (`list_transfers`), and load that into BigQuery to train your models.

The agent can handle quoting, checking rates via `get_exchange_rate`, and listing recipients. It covers both real-time data retrieval and historical record keeping through this MCP Server.

It is. The tool `list_balances` provides a comprehensive snapshot, giving you immediate visibility into all your accounts simultaneously within your enterprise workflow.

The server handles critical financial records, including multi-currency balances (`list_balances`), transfer logs (`list_transfers`), and account statements (`list_statements`).

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