How to Use the FRED Tags & Sources — Data Discovery MCP in Google ADK

Q: How do I install the FRED Tags & Sources — Data Discovery MCP Server for Google ADK?

Run pip install google-adk and set up your McpToolset using the provided endpoint URL. Pass that toolset directly into the tools array of your LlmAgent.

Q: Can I limit which tools my Gemini agent sees from the FRED Tags & Sources — Data Discovery MCP Server?

You absolutely can. Use the toolnames filter when initializing the toolset to expose only searchtags while hiding the others.

Q: How does the agent know which tags to combine?

It queries searchtags first to build a vocabulary of available labels. Then it passes that validated list into getseriesbytags to execute the final search.

Feed official macroeconomic metadata directly into your Google ADK enterprise agents.

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Connect FRED Tags & Sources — Data Discovery MCP to Google ADK

Create your Vinkius account to connect FRED Tags & Sources — Data Discovery 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 Tags & Sources — Data Discovery with Google ADK

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Find economic series via tag intersections

The `get_series_by_tags` tool allows your agent to query the FRED index using specific taxonomy labels. It accepts strings like "inflation" and "monthly" to return exact matches. The agent narrows down millions of data points to a handful of relevant series IDs. Enterprise agents on Google Cloud need exact targeting before moving data. Your agent uses these tags to identify the right macroeconomic indicators. It then pulls those specific series into BigQuery for deeper analysis against your internal metrics.

Search the official taxonomy directly

Exposing the `search_tags` tool gives your agent a way to browse geographic and topic labels. It searches for text strings to find the official St. Louis Fed terminology. The agent learns that "united states" might be tagged simply as "usa". Gemini models have massive context windows. Your agent dumps thousands of tags into memory and reasons about the best combination. You restrict access using the `tool_names` filter in Google ADK if you only want the agent searching tags without listing sources.

Wire the MCP Server to Google ADK

The `list_sources` tool fetches the 107 official institutions providing data to FRED. Your agent reads this registry to verify data provenance. It checks if a series comes from the BEA or a third-party publisher. Setup takes two minutes. You initialize a `McpToolset` with `StreamableHttpServerParameters` and pass it to your `LlmAgent`. The integration natively supports HTTP transports, getting your Gemini models talking to the metadata endpoints immediately.

Setup guide

Set up FRED Tags & Sources — Data Discovery 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 Tags & Sources — Data Discovery 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 Tags & Sources — Data Discovery_agent",
    model="gemini-2.0-flash",
    instruction="You have access to FRED Tags & Sources — Data Discovery tools via MCP.",
    tools=mcp_tools,
)

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Common questions about FRED Tags & Sources — Data Discovery MCP in Google ADK

Run `pip install google-adk` and set up your `McpToolset` using the provided endpoint URL. Pass that toolset directly into the `tools` array of your `LlmAgent`.

You absolutely can. Use the `tool_names` filter when initializing the toolset to expose only `search_tags` while hiding the others.

The tools handle the discovery phase by returning exact series IDs and source metadata. Your Google ADK agent takes those IDs and uses its native GCP capabilities to route the actual data into BigQuery.

It queries `search_tags` first to build a vocabulary of available labels. Then it passes that validated list into `get_series_by_tags` to execute the final search.

No. The infrastructure runs on ephemeral, zero-trust architecture. You are only pulling public BLS and Census Bureau taxonomy data, and the execution environment is wiped clean the moment your HTTP transport closes.

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