How to Use the Mercury MCP in Google ADK

Q: Can I filter Mercury tools in Google ADK?

You can use the toolnames filter to expose only the functions you need. This keeps your agent's scope narrow and secure.

Bridge your Google ADK agents to Mercury banking. Execute financial queries and manage recipients inside your GCP environment.

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Connect Mercury MCP to Google ADK

Create your Vinkius account to connect Mercury 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 Mercury with Google ADK

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Direct Mercury access for Google ADK

Link your GCP-based agents to your bank data using the `McpToolset`. It pulls your account state into the agent's context in seconds. Use `list_accounts` to map your financial structure. Your agent now sees what you see, right in the terminal.

High-volume transaction analysis

Your agent can chew through large sets of history using `list_transactions`. It's built for the long-context capabilities of Gemini. Get granular insights by calling `get_transaction` on specific IDs. It turns your banking history into actionable data for your infrastructure.

Dynamic recipient updates

The agent can manage your payment ecosystem using `create_recipient` and `list_recipients`. It's a clean way to handle vendor onboarding at scale. Keep your logic specific to your business rules. Use the Google ADK tool filtering to restrict which actions the agent can trigger.

Setup guide

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

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Common questions about Mercury MCP in Google ADK

Initialize the McpToolset with your server URL. Then, pass the set to your LlmAgent to start making calls.

The server provides the data, and your agent handles the handoff. You can pipe the `list_transactions` output straight into your BigQuery tables.

You can use the tool_names filter to expose only the functions you need. This keeps your agent's scope narrow and secure.

The server supports both HTTP and Stdio transports. Choose the one that matches your specific GCP deployment strategy.

Access is governed by your Vinkius endpoint token. The agent only reads the transaction and account data you explicitly authorize.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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Google ADK sdk-python

Pydantic AI sdk-python

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Mastra AI sdk-typescript

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