How to Use the IBAN Bank Validator MCP in Google ADK

Q: How do I register the IBAN Bank Validator toolset in Google ADK?

You initialize the McpToolset with the Vinkius HTTP endpoint in your Python script. Pass this toolset directly to your LlmAgent to let Gemini call the validateiban tool whenever it detects an account number.

Verify account numbers directly within your Google ADK pipelines before writing transactions to BigQuery.

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Connect IBAN Bank Validator MCP to Google ADK

Create your Vinkius account to connect IBAN Bank Validator 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 IBAN Bank Validator with Google ADK

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Run Modulus 97 checks inside your Google ADK agent

Invoking the `validate_iban` tool lets your Gemini-powered agent run ISO 13616 calculations on raw strings. It converts the letters to digits and runs the math directly inside your enterprise data flow. This process stops invalid account numbers from ever hitting your BigQuery tables. By catching structural typos early, you avoid dirtying your data warehouse with failed transaction records.

Secure database cleanup with this MCP Server

Exposing the `validate_iban` tool to your Python environment gives your agent a mathematical gatekeeper. You can pass raw strings from your legacy databases directly to the validator before running migration scripts. The tool operates without needing access to your cloud credentials. Your agent simply routes the string to the sandbox, checks the output, and updates your Vertex AI pipeline based on the result.

Multi-country validation in Google ADK

Calling the `validate_iban` tool within your agent workflows lets you parse large batches of transaction logs. The tool handles over 80 country formats natively, matching the length and checksum rules for each region. Your agent can parse thousands of lines of context and use the tool to flag invalid bank routing codes. This ensures your automated financial audits run with absolute mathematical precision.

Setup guide

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

Get your connection token →

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

You initialize the `McpToolset` with the Vinkius HTTP endpoint in your Python script. Pass this toolset directly to your `LlmAgent` to let Gemini call the `validate_iban` tool whenever it detects an account number.

Yes, your agent can loop through multiple strings found in your BigQuery tables and validate each one. The backend MCP Server handles the Modulus 97 calculations instantly to keep your pipeline moving.

No, this MCP Server runs in a secure sandbox outside your Google Cloud project. You only need your Vinkius connection token to let your agent query the validator.

The engine supports all ISO 13616 standard formats across more than 80 countries. It checks both the character length and the mathematical checksum.

Every IBAN string sent through the tool is processed in an ephemeral V8 sandbox that is destroyed immediately after execution. The server never writes your bank routing codes to persistent storage, ensuring zero-trust security.

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