How to Use the Stark Bank MCP in Google ADK

Q: Can Google ADK help with Stark Bank payment processing?

Yes. An agent can use starkcreatepixcharge or starkcreatetransfer after analyzing large datasets in BigQuery. It’s ideal for complex, multi-step financial workflows.

Q: Can I check my current balance using Stark Bank with Google ADK?

You can use starkgetbalance to get the real-time cash total. Gemini models then take that figure and reason about its implications against historical spending patterns.

Analyze enterprise finance data with Google ADK and Gemini models.

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Connect Stark Bank MCP to Google ADK

Create your Vinkius account to connect Stark Bank to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Stark Bank with Google ADK

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Review Payment Histories

Need to audit transactions? Your agent can pull payment history for both outgoing transfers (`stark_list_transfers`) and incoming Pix charges using `stark_list_pix_charges`. This gives a clean, consolidated view of all cash movements.

Determine Available Cash Flow

The agent reads the current balance via `stark_get_balance` and can also fetch historical details using `stark_get_statement`. This massive context allows Gemini to reason over months of financial data for deep insights.

Consolidate Payment Records

The agent manages receivables by listing all Boletos with `stark_list_boletos`, and outgoing payments via `stark_list_transfers`. By combining these lists, you get a full picture of current accounts payable and receivable.

Setup guide

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

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

The native integration allows your agents to act on data already residing in BigQuery. You pass the MCP Toolset, letting Gemini reason over both the tool's output and your existing cloud data.

Yes. An agent can use `stark_create_pix_charge` or `stark_create_transfer` after analyzing large datasets in BigQuery. It’s ideal for complex, multi-step financial workflows.

The key power here is long-context reasoning (1M+ tokens). You can give your agent massive amounts of data and ask it to spot anomalies across different payment tools.

This server touches raw transaction details, including statement records. Because the system runs on Google Cloud infrastructure, you benefit from enterprise-grade security controls and compliance features.

You can use `stark_get_balance` to get the real-time cash total. Gemini models then take that figure and reason about its implications against historical spending patterns.

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