How to Use the CD Return Calculator MCP in Google ADK

Give your Google ADK agents the exact math needed to evaluate certificate of deposit returns.

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Connect CD Return Calculator MCP to Google ADK

Create your Vinkius account to connect CD Return Calculator 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 CD Return Calculator with Google ADK

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Calculate yields across massive datasets

Your BigQuery-connected agent uses `calculate_cd_yield` to compute compounding interest on thousands of rows of financial data. You feed it the term and rate. The MCP handles the daily or monthly compounding math automatically. Let's be real. Doing this manually in SQL is a nightmare. Your Gemini models can now pull customer deposit records, run the yield math, and write the projections right back into your cloud database.

Pull market benchmarks instantly

The `fetch_market_benchmarks` tool gives your agent hardcoded high-yield savings account and money market rates. It checks the current interest rate environment and returns the corresponding liquid alternatives. Long-context reasoning shines when you have 1 million tokens to play with. You can dump ten years of historical rate data into the prompt. The agent compares those historical trends against the current benchmarks without losing track of the details.

Build Google ADK investment models

Generating a high-level overview of different assets happens through `generate_investment_comparison`. This operation puts the locked deposit yield next to the liquid market alternatives. The math doesn't lie. You can filter which operations the agent sees using the tool names parameter in your setup. Restrict the agent to just the comparison function if you want to limit its scope. That keeps enterprise deployments focused and predictable.

Setup guide

Set up CD Return Calculator 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 CD Return Calculator 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="CD Return Calculator_agent",
    model="gemini-2.0-flash",
    instruction="You have access to CD Return Calculator 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 CD Return Calculator. 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 CD Return Calculator MCP in Google ADK

Run pip install google-adk first. Initialize an McpToolset using streamable HTTP parameters with your Vinkius endpoint. Pass that toolset directly to your LlmAgent.

Yes, your agent can read financial records from BigQuery and pass those values to the MCP. It then writes the resulting yield calculations back to your tables.

You can use the optional tool names filter when setting up the toolset. This restricts the LlmAgent to specific financial functions instead of exposing the entire catalog.

The massive token limit allows you to feed complex financial histories into the prompt. The agent will use the MCP to calculate returns based on that deep contextual data.

The MCP only touches the specific deposit amounts and rate variables you send it. All traffic routes through encrypted HTTP transports. Your raw database credentials never leave your local Google Cloud environment.

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