How to Use the BLS Jobs — Nonfarm Payrolls & Wages MCP in Google ADK

Q: How do I connect BLS Jobs — Nonfarm Payrolls & Wages to Google ADK?

Initialize the toolset using McpToolset with your Vinkius HTTP endpoint. Pass this MCP toolset to your LlmAgent to expose the payroll tools.

Q: How do I restrict which BLS Jobs — Nonfarm Payrolls & Wages tools my Google ADK agent can use?

Use the optional toolnames filter when setting up your toolset. You can restrict the agent to just getnonfarmpayrolls to prevent unauthorized series queries.

Run Gemini models over massive BLS Jobs — Nonfarm Payrolls & Wages datasets directly inside your Google ADK pipelines.

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Connect BLS Jobs — Nonfarm Payrolls & Wages MCP to Google ADK

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Setup BLS Jobs — Nonfarm Payrolls & Wages with Google ADK

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Combine Google ADK with BLS Jobs

The `get_nonfarm_payrolls` tool pulls the CES0000000001 series directly into your Google ADK Gemini model's active context window. This setup lets you process years of historical employment data at once. You can cross-reference payroll records against your private market data stored in BigQuery. Automated reasoning over macroeconomic trends becomes straightforward within the Google Cloud ecosystem.

Run bulk timeseries queries with Google ADK

The `query_bls` tool processes up to 50 employment series at once to feed your Google ADK enterprise data pipelines. Raw government connections are handled by the MCP Server, while your Google Cloud infrastructure manages the data flow. You can filter exposed tools using the `tool_names` parameter in your ADK setup. This ensures your Gemini agent only touches the specific payroll metrics needed for your current analysis.

Feed clean labor data to enterprise pipelines

This MCP Server connects your Google ADK agent directly to the live BLS database via Streamable HTTP. The agent calls `get_nonfarm_payrolls` to feed fresh economic indicators directly into your Vertex AI models. No intermediate database is required to fetch these labor metrics. Your enterprise agents pull live payroll data on demand, keeping your interest rate forecasts accurate.

Setup guide

Set up BLS Jobs — Nonfarm Payrolls & Wages 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 Jobs — Nonfarm Payrolls & Wages 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 Jobs — Nonfarm Payrolls & Wages_agent",
    model="gemini-2.0-flash",
    instruction="You have access to BLS Jobs — Nonfarm Payrolls & Wages tools via MCP.",
    tools=mcp_tools,
)

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Common questions about BLS Jobs — Nonfarm Payrolls & Wages MCP in Google ADK

Initialize the toolset using `McpToolset` with your Vinkius HTTP endpoint. Pass this MCP toolset to your `LlmAgent` to expose the payroll tools.

Yes, Gemini's million-token context allows you to feed decades of raw data from `query_bls` directly into a single prompt for deep trend analysis.

Use the optional `tool_names` filter when setting up your toolset. You can restrict the agent to just `get_nonfarm_payrolls` to prevent unauthorized series queries.

The MCP toolset supports both Stdio and HTTP transports, making it easy to run your labor market agents inside Google Cloud Run.

Your BLS Series IDs and payroll lookup parameters are processed in an isolated V8 sandbox. No query history or credentials are ever logged or shared.

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