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

Q: How do I configure EIA Petroleum — Oil Market Intelligence MCP Server in Cursor?

Create an mcp.json file in your project root directory. Add the server details under mcpServers. Toggle Agent mode on in the chat panel to let the AI call the tools.

Code trading algorithms in Cursor using live U.S. crude production and import data.

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Connect EIA Petroleum — Oil Market Intelligence MCP to Cursor

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

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Inject live market data into Cursor via MCP

Writing pricing models requires real inputs, not mocked JSON. Agent mode connects directly to this MCP Server to pull actual WTI numbers while you type. You tell the editor to build a forecasting function, and it uses `get_petroleum_prices` to structure the exact data types the EIA returns. This changes how you test logic. Your AI client writes a script to calculate supply deficits, calling `get_petroleum_summary` to check the weekly status report format. The code works on the first run because the agent built it against the live endpoint.

Model refinery operations and stock levels

Energy sector developers spend hours mapping government data structures. You skip that entirely. Ask Cursor to create a dashboard backend, and it runs `get_refinery_operations` to see the actual capacity fields. It maps the utilization rates perfectly. Adding inventory tracking takes seconds. The agent uses `get_petroleum_stocks` to check commercial and Strategic Petroleum Reserve levels. It writes the database schema matching the exact EIA output, saving you from reading outdated API documentation.

Build trade flow trackers mid-code

Tracking physical barrels requires complex joins. You can prompt your editor to write a script analyzing import reliance. The agent fires `get_crude_imports` to inspect the country-of-origin fields, then writes the Python pandas logic to aggregate the grades. It handles domestic output just as easily. Cursor calls `get_crude_production` to pull U.S. reserves data, then merges it with `get_petroleum_trade` metrics. You get a complete supply chain script without leaving your IDE.

Setup guide

Set up EIA Petroleum — Oil Market Intelligence MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the EIA Petroleum — Oil Market Intelligence MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent EIA Petroleum — Oil Market Intelligence transactions." If the MCP tools are loaded correctly, Cursor will call the EIA Petroleum — Oil Market Intelligence tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "eia-petroleum-oil-market-intelligence-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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

Create an `mcp.json` file in your project root directory. Add the server details under `mcpServers`. Toggle Agent mode on in the chat panel to let the AI call the tools.

Yes. The agent pulls live diesel prices and consumption stats to populate your test fixtures. You test against actual market conditions instead of fake placeholder strings.

Yes. The agent runs the consumption tool to pull sales by product and sector. It can then write the exact API calls you need to fetch that specific data in your own app.

The server exposes the exact supply and demand balance through a dedicated tool. Your editor can inspect this payload to auto-generate the TypeScript interfaces for your frontend.

Your algorithms never leave your machine. The server strictly gets external metrics like crude imports and refinery utilization. Cursor processes the JSON locally, ensuring your proprietary logic remains secure.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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