How to Use the FRED Series — U.S. Economic Time Series MCP in Google ADK

Q: Can Google ADK agents filter FRED Series — U.S. Economic Time Series data by specific vintage dates?

Yes, you can call getvintagedates to retrieve the revision history. Your Google ADK agent can then query observations for specific vintages to replicate historical economic models accurately.

Q: Does FRED Series — U.S. Economic Time Series support regional economic data in Google ADK?

Yes, you can use searchseries to find state, county, or MSA-level data. Your Google ADK agent can then fetch these regional observations for localized economic analysis.

Q: What happens if a query returns too many data points?

You should use the frequency aggregation parameter in getobservations to downsample the data. This keeps the response payload small and prevents your agent from hitting token limits.

Feed clean economic time series data directly to your Google ADK enterprise agents on Vertex AI.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect FRED Series — U.S. Economic Time Series MCP to Google ADK

Create your Vinkius account to connect FRED Series — U.S. Economic Time Series 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.

GDPR Free for Subscribers

Setup FRED Series — U.S. Economic Time Series with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Target Specific Macro Series in Google ADK

The `get_series` tool retrieves metadata for well-known indicators like FEDFUNDS or DGS10 directly into your Google ADK workflow using our MCP connection. This tool identifies the frequency, units, and seasonal adjustment status of the target series before you run deep analysis. Your enterprise agents can use this metadata to format BigQuery schemas or prepare Vertex AI pipelines. It ensures your data pipelines always align with official federal reporting structures.

Fetch Aggregated Economic Observations

The `get_observations` tool extracts the actual data points for any series with optional date filters and frequency aggregation. Your Google ADK agent can request monthly, quarterly, or annual rollups on the fly. This direct data pull bypasses the need for manual ETL pipelines. The Gemini long-context window can easily ingest decades of aggregated macro data for deep economic forecasting.

Track Real-Time Macro Updates with this MCP Server

The `get_series_updates` tool monitors the latest economic releases, filtering by macro or regional indicators. This tool lets your Google ADK agents trigger automated workflows the moment the government releases new employment or inflation figures. You can connect these triggers to your cloud databases to keep your internal dashboards updated. It eliminates the delay between federal releases and your business intelligence systems.

Setup guide

Set up FRED Series — U.S. Economic Time Series 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 Series — U.S. Economic Time Series 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 Series — U.S. Economic Time Series_agent",
    model="gemini-2.0-flash",
    instruction="You have access to FRED Series — U.S. Economic Time Series tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by FRED. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect FRED Series — U.S. Economic Time Series now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about FRED Series — U.S. Economic Time Series MCP in Google ADK

You set the API key in the Vinkius console when configuring the MCP server. Your Google ADK client connects using a single secure endpoint token, keeping your actual FRED credentials hidden from your agent code.

Yes, you can call `get_vintage_dates` to retrieve the revision history. Your Google ADK agent can then query observations for specific vintages to replicate historical economic models accurately.

Yes, you can use `search_series` to find state, county, or MSA-level data. Your Google ADK agent can then fetch these regional observations for localized economic analysis.

You should use the frequency aggregation parameter in `get_observations` to downsample the data. This keeps the response payload small and prevents your agent from hitting token limits.

Absolutely. All communication between the FRED Series MCP Server, the FRED API, and your Google ADK environment is encrypted in transit via HTTPS, ensuring your economic queries remain completely private.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript