How to Use the EIA Petroleum — Oil Market Intelligence MCP in LangChain

Build smarter economic agents on LangChain with live oil market data.

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Connect EIA Petroleum — Oil Market Intelligence MCP to LangChain

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

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Market Indicators

Your agent can see a price spike with `get_petroleum_prices` and immediately check inventories using `get_petroleum_stocks`. This isn't a fixed script; it's a dynamic chain of reasoning where one tool's output triggers the next logical step. This is the ReAct framework in action. If inventories look fine, the agent might pivot to check `get_refinery_operations` for bottlenecks. You're building an agent that doesn't just follow orders, it investigates.

Model the Full Supply Chain

Give your LangChain agent the power to model the entire U.S. petroleum market. It can pull crude production numbers with `get_crude_production`, track imports with `get_crude_imports`, and monitor demand using `get_petroleum_consumption`. Then, have the agent pull the official `get_petroleum_summary` report. It can compare its own derived balance against the EIA's weekly numbers. This is how you validate your agent's understanding of the market.

Your LangChain Agent's New Tools

Getting started is simple. Pass the list of EIA tools to your agent and it knows what to do. It understands how to fetch WTI prices with `get_petroleum_prices` or get SPR levels from `get_petroleum_stocks`. Because it's LangChain, you can combine these tools with any other data source. Mix real-time oil data from this MCP Server with your company's internal logistics data or a vector database of news reports. It all works together in one chain.

Setup guide

Set up EIA Petroleum — Oil Market Intelligence MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes EIA Petroleum — Oil Market Intelligence tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "eia-petroleum-oil-market-intelligence-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent EIA Petroleum — Oil Market Intelligence transactions"
    })
    print(result["messages"][-1].content)

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Common questions about EIA Petroleum — Oil Market Intelligence MCP in LangChain

You get the tools from the client and pass them into your agent's constructor. LangChain's `create_agent` function automatically makes the EIA tools available for the agent to call based on its objective.

Yes. You can put the EIA tools in the same agent that has access to a SQL database, a vector store, or any of the other 500+ integrations. The agent will decide which tool is best for the job at hand.

A chain is a fixed sequence of calls, like 'get prices, then get stocks'. An agent is dynamic; it decides whether to call `get_prices` or `get_stocks` based on the user's prompt and its own reasoning.

If an EIA tool call fails, the error is passed back to the LangChain agent. You can program the agent to handle it—for example, by trying the call again or using a different tool to find the information.

Your LangChain agent requests public EIA petroleum data—like prices, stock levels, and production figures. Each request you make runs in a Vinkius ephemeral sandbox, which is destroyed after your call completes. We don't log or store the data you access.

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