How to Use the FIRE Calculator MCP in Google ADK

Q: Can I limit which FIRE Calculator tools Google ADK exposes?

You restrict access using the optional toolnames filter. This prevents the agent from running complex simulations if you only want it to check basic milestones.

Connect the FIRE Calculator to Google ADK and run retirement simulations across your enterprise data.

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Connect FIRE Calculator MCP to Google ADK

Create your Vinkius account to connect FIRE 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 FIRE Calculator with Google ADK

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Map BigQuery Data to FIRE Lifestyle

This MCP bridges your internal financial data with early retirement models. Your agent extracts current user spending from BigQuery and feeds it into `get_lifestyle_targets` to define the exact portfolio size required. The long-context window lets you feed years of transaction history into the prompt. Agents analyze the actual spending trends rather than relying on the user to guess their budget.

Run Enterprise-Grade Retirement Timelines

Building a wealth management assistant requires exact math. The `calculate_milestones` endpoint generates strict timelines for Lean, Standard, and Fat FIRE based on current assets. Your agent processes these milestones alongside macroeconomic data stored in Google Cloud. This MCP gives the user a realistic timeline adjusted for actual market conditions.

Simulate Scenarios with Google ADK

Changing a savings rate by two percent changes everything. You trigger `simulate_contribution_impact` to calculate the exact month the portfolio reaches critical mass under different saving regimes. The framework parses the results and generates a clear comparative analysis. You show the client exactly what happens if they cut their discretionary spending today.

Setup guide

Set up FIRE 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 FIRE 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="FIRE Calculator_agent",
    model="gemini-2.0-flash",
    instruction="You have access to FIRE Calculator tools via MCP.",
    tools=mcp_tools,
)

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Common questions about FIRE Calculator MCP in Google ADK

Install the package and configure a StreamableHttpServerParameters object with your Vinkius endpoint. Pass it to McpToolset and attach it to your LlmAgent.

You restrict access using the optional tool_names filter. This prevents the agent from running complex simulations if you only want it to check basic milestones.

The integration thrives on massive context. You load decades of market data into the prompt while relying on the MCP to handle the strict compounding calculations.

The setup supports both Stdio and HTTP transports. Vinkius provides a secure HTTP endpoint that connects directly to your cloud infrastructure.

The FIRE Calculator receives total asset balances and monthly contribution numbers. Vinkius isolates each execution environment. The data vanishes the millisecond the HTTP response completes.

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