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How to Use the Wave Financial MCP in Google ADK

Scale Your Accounting Operations with Wave Financial via Google ADK’s Enterprise Agent Framework.

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Google ADK

Connect Wave Financial MCP to Google ADK

Create your Vinkius account to connect Wave Financial 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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Deep Data Querying for Transactions

You can list every accounting transaction using `list_transactions`. This is critical for big data tasks because the Gemini models behind this agent can handle massive context windows, holding 1M+ tokens. It allows your agents to correlate transactions with other data sources you have in BigQuery, making the financial picture much clearer.

Comprehensive Customer and Vendor Records

The agent lists all customers via `list_customers` and tracks vendors using `list_vendors`. Because this is built on Google Cloud infrastructure, these lists are designed to scale with your enterprise needs. It’s perfect for building agents that need a holistic view of who you do business with—both selling and buying sides.

MCP Server Integration in BigQuery Ecosystem

The Google ADK provides native integration points with BigQuery, letting your agent act on Wave Financial data *and* other enterprise assets. This isn't just a query; it’s an operational workflow. It means you don't have to export and load data separately. The agent performs actions across connected systems using the MCP Server.

Setup guide

Set up Wave Financial 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. 1

    Install Google ADK

    Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.

  2. 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. 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. 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 Wave Financial 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="Wave Financial_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Wave Financial tools via MCP.",
    tools=mcp_tools,
)

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

You call `list_customers`. This tool pulls all necessary client records for a specific business, giving your agent the exact list it needs to proceed with an operation.
Yes. Use `list_accounts` to see the entire chart of accounts for a business. The Google ADK handles this data retrieval smoothly, even with complex setups.
The server supports ten core tools, including listing invoices (`list_invoices`), products (`list_products`), and sales taxes. This range lets your agents cover most financial operations.
Since it uses native integration points, yes. The agent processes structured data like transactions and accounts directly into the Google Cloud environment for processing.
The primary data types handled include `list_transactions` records. Because of BigQuery integration, you can correlate these transactions with other large datasets.

Start using the Wave Financial MCP today

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Built & Managed by Vinkius 30s setup 10 tools

We've already built the connector for Wave Financial. Just plug in your AI agents and start using Vinkius.

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