How to Use the BLS Wages — OEWS Occupational Employment MCP in OpenAI Agents SDK
Pull precise salary data directly into your OpenAI Agents SDK workflow to build reliable, data-backed hiring models.
Works with every AI agent you already use
…and any MCP-compatible client
Connect BLS Wages — OEWS Occupational Employment MCP to OpenAI Agents SDK
Create your Vinkius account to connect BLS Wages — OEWS Occupational Employment to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Direct `query_bls` access for OpenAI Agents SDK
Your agent needs raw numbers to make smart hiring decisions. This MCP server lets your Python code pull median earnings for specific roles and states without leaving your agent loop. Using `query_bls` is straightforward. You feed it the exact series ID, and the agent gets the raw wage data back instantly for processing.
Production-grade wage lookups
Stop guessing what developers or analysts make in specific regions. Your agent hits the OEWS database to pull real figures that inform your budget planning. Because this is an MCP server, your agent handles the data flow within your existing guardrails. It validates the output against your safety constraints before you deploy any hiring logic.
High-concurrency data retrieval
You can fire off up to 50 concurrent lookbacks when your agent needs a bulk salary report. It handles the heavy lifting while your agent stays responsive. Tracing this in your OpenAI dashboard is simple. You see exactly when the agent calls `query_bls` and what it does with the resulting wage statistics.
Set up BLS Wages — OEWS Occupational Employment MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all BLS Wages — OEWS Occupational Employment tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives BLS Wages — OEWS Occupational Employment tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate BLS Wages — OEWS Occupational Employment tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="BLS Wages — OEWS Occupational Employment Agent",
instructions="You have access to BLS Wages — OEWS Occupational Employment tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) 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.
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Common questions about BLS Wages — OEWS Occupational Employment MCP in OpenAI Agents SDK
Use it with your favorite AI tools
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Start using the BLS Wages — OEWS Occupational Employment MCP today
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