How to Use the Codat Financial Data MCP in Google ADK

Q: How do I initialize the Codat Financial Data MCP Server inside Google ADK?

Install the package via pip install google-adk and create an McpToolset pointing to your Vinkius HTTP endpoint. Pass this toolset directly to your LlmAgent in the tools parameter. This exposes all twelve financial tools to Gemini without any manual schema mapping.

Q: How do I restrict which Codat Financial Data tools are exposed to my Google ADK agent?

Use the toolnames filter when initializing your McpToolset to limit exposure. For example, pass only listaccountingcustomers if you want to prevent your agent from accessing banking transactions. This keeps your Google Cloud environment secure and compliant.

Feed clean Codat banking and commerce data directly to Gemini models and BigQuery using the Google ADK.

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Connect Codat Financial Data MCP to Google ADK

Create your Vinkius account to connect Codat Financial Data 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 Codat Financial Data with Google ADK

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Map Bank Feeds to BigQuery with Google ADK

Your Gemini agent pulls raw financial records by executing `list_banking_transactions` to fetch clean bank feeds. This tool exposes transaction histories from multiple institutions in a single standardized format. Because Google ADK integrates directly with Google Cloud, your agent writes these records straight into a BigQuery table for long-term analytics.

Audit Accounting Invoices in This MCP Server

Extracting customer ledger bills requires running `list_accounting_invoices` to retrieve standardized invoice data. This tool queries the underlying accounting software to pull balances, payment status, and customer details. Your Google ADK agent analyzes these invoice lists to identify outstanding liabilities.

Track Active Integrations inside Google Cloud

Verifying platform availability starts with running `list_supported_integrations` to fetch all active platforms. This tool lists every accounting, banking, and commerce system currently connected to your Codat instance. Your Gemini agent uses this list to determine if a new client is eligible to connect their ledger.

Setup guide

Set up Codat Financial Data 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 Codat Financial Data 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="Codat Financial Data_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Codat Financial Data tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Codat Financial Data MCP in Google ADK

Install the package via `pip install google-adk` and create an `McpToolset` pointing to your Vinkius HTTP endpoint. Pass this toolset directly to your `LlmAgent` in the tools parameter. This exposes all twelve financial tools to Gemini without any manual schema mapping.

Use the `tool_names` filter when initializing your `McpToolset` to limit exposure. For example, pass only `list_accounting_customers` if you want to prevent your agent from accessing banking transactions. This keeps your Google Cloud environment secure and compliant.

The Google ADK allows Gemini to process over a million tokens, meaning Gemini processes over a million tokens and pulls thousands of rows using `list_commerce_transactions` in a single run. The model inspects entire commerce ledger histories at once to find complex patterns. You do not have to build complex chunking or retrieval strategies.

Use either Stdio or Streamable HTTP transports to connect your MCP server to Vinkius. Most enterprise Google Cloud deployments use the Streamable HTTP transport for better scalability. This allows your server to run in a zero-trust sandbox while your agent executes queries.

Your customer's balance sheets and commerce transactions are protected by Google Cloud's enterprise-grade security layers. The MCP server communicates with Vinkius using encrypted HTTP tunnels, and the data is processed directly inside your VPC. No financial data is ever used to train public Gemini models.

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