How to Use the Exchange Rates API MCP in Google ADK

Q: Can I restrict which Exchange Rates API tools my Google ADK agent can use?

You can. The toolnames filter in the McpToolset constructor lets you block access to specific tools like historical data if your agent doesn't need them.

Connect your Google ADK agents to live currency markets for automated financial operations.

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Connect Exchange Rates API MCP to Google ADK

Create your Vinkius account to connect Exchange Rates API 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 Exchange Rates API with Google ADK

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Instant rate retrieval for Google ADK

Your agents can pull the latest market status with `get_latest_exchange_rates`. It bridges the gap between your cloud data and live global currency movements. This gives your Google ADK agent the context it needs to make informed decisions. It eliminates the need for daily manual updates.

Time-series data for Google ADK agents

Use `get_exchange_rate_timeseries` to feed historical price data into your reasoning engine. Your agent can analyze patterns over specific windows with minimal latency. It works well with large context windows. You can pipe weeks of rate history into your model and let it summarize the financial outlook for your team.

Currency discovery for Google ADK workflows

The `list_supported_currencies` tool lets your agent query the full list of available codes. This ensures your agent always knows which symbols are valid before it tries to convert them. It prevents errors by verifying inputs against the live API registry. Your agent stays in sync with the current list of supported markets automatically.

Setup guide

Set up Exchange Rates API 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 Exchange Rates API 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="Exchange Rates API_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Exchange Rates API tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Exchange Rates API MCP in Google ADK

It is. You simply use the McpToolset class to define the server endpoint. Your LLM agent will then have direct access to all 7 conversion and history tools.

You can. The tool_names filter in the McpToolset constructor lets you block access to specific tools like historical data if your agent doesn't need them.

You should wrap your tool calls in standard try-except blocks. If the request fails, the agent can log the error and decide whether to retry or move on.

The server runs in an isolated V8 sandbox. It only executes the specific tool call requested and doesn't have broader access to your Google Cloud environment.

It provides public currency symbols, real-time conversion rates, and historical logs. No internal or user-specific financial information ever enters the pipeline.

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