How to Use the FRED GeoFRED — Regional Economic Data MCP in Google ADK

Q: Can Google ADK agents filter tools from FRED GeoFRED — Regional Economic Data?

Yes, use the toolnames filter during initialization to restrict access. This is useful if your agent only needs specific functions like data retrieval and not shape file access.

Connect your Google ADK agents to the official FRED GeoFRED database for enterprise-grade regional economic insights.

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Connect FRED GeoFRED — Regional Economic Data MCP to Google ADK

Create your Vinkius account to connect FRED GeoFRED — Regional Economic 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 FRED GeoFRED — Regional Economic Data with Google ADK

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Query granular regional metrics with Google ADK

Your agent can now pull specific county or metro-level data by calling `get_regional_data` directly. It bridges the gap between your cloud data warehouse and the latest Federal Reserve economic releases. This setup allows for direct analysis within your existing Google Cloud infrastructure. You spend less time moving files and more time interpreting the local economic trends.

Automate map generation for your agents

Use `get_geo_shapes` to retrieve boundary data for any U.S. region. Your agent processes these shapes to build maps that visualize economic performance across states or FRB districts. This is ideal for building automated reporting tools that track regional health. The agent handles the data retrieval while you define how the maps display in your dashboard.

Validate series configurations before data fetching

Call `get_series_group` to identify the right parameters for your economic series. Your agent uses this to confirm that the region type and units match the data you need for your Google ADK agent. This step eliminates errors before you run a full analysis. It ensures your agent operates on clean, consistent data from the start.

Setup guide

Set up FRED GeoFRED — Regional Economic 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 FRED GeoFRED — Regional Economic 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="FRED GeoFRED — Regional Economic Data_agent",
    model="gemini-2.0-flash",
    instruction="You have access to FRED GeoFRED — Regional Economic Data tools via MCP.",
    tools=mcp_tools,
)

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Common questions about FRED GeoFRED — Regional Economic Data MCP in Google ADK

Install the package and initialize an McpToolset using your server's URL. Once configured, pass the toolset to your LlmAgent to start querying economic data.

Yes, use the tool_names filter during initialization to restrict access. This is useful if your agent only needs specific functions like data retrieval and not shape file access.

It does. You can pull massive regional datasets into the agent's context window. This allows the model to reason over years of economic history across multiple counties.

Deploy the server as a sidecar or a reachable HTTP service. Your agent then communicates with it via standard HTTP transport as defined in your setup.

The server acts as a pass-through for public economic records. No sensitive user information is ever requested or processed; we only handle public-facing FRED economic series.

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