How to Use the FRED Categories — Economic Data Taxonomy MCP in Google ADK

Q: Does Google ADK support tool filtering for FRED Categories — Economic Data Taxonomy?

Yes. You can use the toolnames filter to expose only the tools your agent actually needs. This keeps your agent's action space simple.

Connect Google ADK agents to real-world economic indicators with the FRED Categories — Economic Data Taxonomy MCP Server.

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Connect FRED Categories — Economic Data Taxonomy MCP to Google ADK

Create your Vinkius account to connect FRED Categories — Economic Data Taxonomy 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 Categories — Economic Data Taxonomy with Google ADK

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Map categories with Google ADK

Your agent uses `get_category_children` to explore the taxonomy hierarchy. It identifies relevant economic segments like money supply or production activity. This allows your agent to navigate the FRED tree dynamically. It builds a mental model of the economic landscape using only the data you need.

Direct series access for Gemini

Call `get_category_series` to fetch specific metrics for your long-context reasoning tasks. The data flows directly into your Gemini-powered agent. You can feed this into BigQuery or other infrastructure. The agent manages the flow of data from the MCP Server into your cloud ecosystem.

Refine metrics using tags

The `get_category_tags` tool lets you filter series by specific economic dimensions. Your agent uses this to narrow down its search results. It makes your agent's reasoning more precise. By ignoring irrelevant tags, it spends fewer tokens and gets better results for your enterprise logic.

Setup guide

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

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Common questions about FRED Categories — Economic Data Taxonomy MCP in Google ADK

Use the McpToolset class in your agent setup. Point it to the server URL, and your agent will have access to all four tools.

You can implement a caching layer in your agent's logic. This helps you stay within API limits while maintaining fast access to the taxonomy.

Yes. You can use the tool_names filter to expose only the tools your agent actually needs. This keeps your agent's action space simple.

There is no hard limit on depth, but you should cache top-level results. This ensures your agent stays responsive when exploring the tree.

The server handles only public metadata and economic series. Your internal Google Cloud data stays separate and is never touched by this tool.

Use it with your favorite AI tools

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