How to Use the EIA Petroleum — Oil Market Intelligence MCP in OpenAI Agents SDK

Q: Can an agent built with OpenAI Agents SDK execute trade decisions using EIA Petroleum — Oil Market Intelligence?

Yes, by combining getpetroleumtrade and getcrudeimports with your agent's execution logic. Built-in SDK guardrails let you inspect and validate the agent's trade recommendations before they execute.

Q: How do I query weekly inventory reports?

Use getpetroleumsummary to pull the latest weekly petroleum status report. Your agent parses this data to analyze the balance between domestic production and consumption.

Feed live WTI, Brent, and SPR levels directly to your OpenAI Agents SDK pipelines with zero-configuration tool discovery.

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Connect EIA Petroleum — Oil Market Intelligence MCP to OpenAI Agents SDK

Create your Vinkius account to connect EIA Petroleum — Oil Market Intelligence 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.

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Setup EIA Petroleum — Oil Market Intelligence with OpenAI Agents SDK

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The `get_petroleum_prices` tool pulls live WTI, Brent, gasoline, and diesel prices directly into your agent's context. Your OpenAI Agents SDK setup auto-discovers this endpoint, letting specialized agents query the price spread without manual configuration. If prices spike, the agent triggers downstream workflows using native OpenAI tracing. This removes the guesswork from monitoring market volatility during active trading sessions.

Map supply bottlenecks via refinery metrics

The `get_refinery_operations` tool exposes capacity, utilization, and processing data to your agentic workflows. By feeding this raw data to a specialized analyst agent, you spot refinery bottlenecks before they impact retail fuel costs. You configure the agent to hand off tasks to a risk-assessment agent when utilization crosses 90 percent. This multi-agent coordination happens entirely within your Python environment using built-in SDK guardrails.

Monitor SPR drawdowns using this MCP Server

The `get_petroleum_stocks` tool retrieves commercial inventories and Strategic Petroleum Reserve levels. Your agent monitors these volumes to detect supply cushions or deficits during geopolitical shocks. The MCP Server passes structured volume data directly to your OpenAI pipeline. Native dashboard tracing shows you exactly what inventory numbers the agent evaluated before recommending a trade position.

Setup guide

Set up EIA Petroleum — Oil Market Intelligence MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all EIA Petroleum — Oil Market Intelligence tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives EIA Petroleum — Oil Market Intelligence tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate EIA Petroleum — Oil Market Intelligence tools and returns structured results. Copy the full example on the right to get started.

agent.py

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="EIA Petroleum — Oil Market Intelligence Agent",
            instructions="You have access to EIA Petroleum — Oil Market Intelligence tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about EIA Petroleum — Oil Market Intelligence MCP in OpenAI Agents SDK

You pass the server URL to the MCPServerStreamableHttp constructor and include it in your Agent's mcp_servers list. The SDK automatically registers all eight tools, including `get_petroleum_summary`, during runtime initialization.

Yes, by combining `get_petroleum_trade` and `get_crude_imports` with your agent's execution logic. Built-in SDK guardrails let you inspect and validate the agent's trade recommendations before they execute.

The MCP Server manages the underlying EIA API connection and handles standard HTTP headers. You should set cacheToolsList to true in your Python code to prevent redundant tool discovery requests.

Use `get_petroleum_summary` to pull the latest weekly petroleum status report. Your agent parses this data to analyze the balance between domestic production and consumption.

This server handles sensitive energy query parameters and API credentials within an isolated V8 sandbox. Your request data, including specific oil import queries, is processed in memory and never written to persistent logs.

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