How to Use the BLS Wages — OEWS Occupational Employment MCP in Google ADK

Feed Google ADK agents real-world wage statistics to power your enterprise hiring analytics on Google Cloud.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect BLS Wages — OEWS Occupational Employment MCP to Google ADK

Create your Vinkius account to connect BLS Wages — OEWS Occupational Employment 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 BLS Wages — OEWS Occupational Employment with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Google ADK integration for wage data

Your Gemini agents can now query the OEWS database for accurate salary benchmarks. Simply register the MCP toolset to give your agent access to `query_bls`. This fits perfectly if your data already lives in BigQuery. Your agent fetches the wage series and writes the results back to your cloud infrastructure.

Long-context reasoning with wage data

Gemini models can chew through massive salary datasets once your agent pulls them in. Use the `query_bls` tool to feed the model specific state-level wage series. Your agent then draws conclusions based on millions of tokens of context. It connects the dots between regional employment trends and your internal hiring needs.

Filtering tools for Google ADK

You keep your agent clean by using the tool_names filter. Only expose `query_bls` if that is all your agent requires for its specific task. This prevents your agent from getting distracted by unnecessary operations. It stays focused on pulling the correct wage statistics from the BLS servers.

Setup guide

Set up BLS Wages — OEWS Occupational Employment 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 Wages — OEWS Occupational Employment 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 Wages — OEWS Occupational Employment_agent",
    model="gemini-2.0-flash",
    instruction="You have access to BLS Wages — OEWS Occupational Employment 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 Bureau of Labor Statistics. 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 BLS Wages — OEWS Occupational Employment 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 BLS Wages — OEWS Occupational Employment MCP in Google ADK

You use the McpToolset class with your server parameters. Once you pass that to your LlmAgent, your agent can call the wage tools directly.

It does. You can choose between Stdio or HTTP transports depending on where your server is running. Most enterprise setups prefer the HTTP approach for flexibility.

Absolutely. Your agent can pull wage data via the MCP tool and then execute SQL queries against BigQuery. It creates a complete pipeline for your HR team.

The server supports up to 50 concurrent lookbacks. This is plenty for most agent-based analysis tasks on Google Cloud.

All traffic between your agent and the server is encrypted in transit. The server only deals with public labor statistics, so no sensitive corporate data is exposed.

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