How to Use the BLS Local — LAUS State & County Unemployment MCP in Google ADK

Feed deep historical county unemployment data directly into your Google ADK pipelines and BigQuery models.

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Connect BLS Local — LAUS State & County Unemployment MCP to Google ADK

Create your Vinkius account to connect BLS Local — LAUS State & County Unemployment 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 BLS Local — LAUS State & County Unemployment with Google ADK

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Inject state metrics into Google ADK pipelines

The `query_bls` tool brings granular county and state unemployment data into your Gemini-powered agent workflows. You feed raw series codes straight to the model, allowing it to parse historical local trends without leaving your cloud workspace. Because Gemini handles massive context windows, you can pull up to 50 series histories at once and let the model find correlations across different metro areas. No need to pre-aggregate the data before the agent analyzes it.

Join BigQuery tables with live MCP Server data

The `query_bls` tool connects your enterprise Google Cloud databases with live labor statistics. Your agent uses the tool to fetch fresh county unemployment rates, then merges them with your existing retail or real estate datasets in BigQuery. This integration bypasses tedious ETL setups. The agent acts as the data engineer, writing the SQL and querying the live government data sources in a single execution loop.

Automate regional analysis with Vertex AI

The `query_bls` tool lets your Vertex-hosted agents monitor regional economic shifts on demand. The agent checks specific LAUS series IDs, processes the timeseries arrays, and generates updated forecasts. You configure the toolset directly within your agent parameters. This keeps your deployment clean, using standard HTTP transport layers to fetch data without maintaining custom API clients.

Setup guide

Set up BLS Local — LAUS State & County Unemployment 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 BLS Local — LAUS State & County Unemployment 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="BLS Local — LAUS State & County Unemployment_agent",
    model="gemini-2.0-flash",
    instruction="You have access to BLS Local — LAUS State & County Unemployment tools via MCP.",
    tools=mcp_tools,
)

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Common questions about BLS Local — LAUS State & County Unemployment MCP in Google ADK

You register the server URL as a streamable HTTP resource in your agent setup. The Gemini model automatically identifies the query tools and calls them when it needs unemployment statistics.

Yes, you can use the tool names filter in the ADK setup to control access. Since this server focuses on the `query_bls` tool, you can expose it exclusively to keep agent actions predictable.

Yes, the MCP Server manages the payload delivery. Your agent can bundle up to 50 series IDs in a single query, which Gemini easily processes thanks to its large context window.

Yes, you can run the server via standard stdio transport locally or connect to the managed Vinkius HTTP endpoint for cloud-based deployments.

Yes, all requests to the endpoint are encrypted in transit. Vinkius does not log the specific series IDs or the returned timeseries datasets, ensuring your regional research strategies remain confidential.

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