How to Use the EIA Petroleum — Oil Market Intelligence MCP in Vercel AI SDK

Q: How do I connect the EIA Petroleum — Oil Market Intelligence MCP Server to Vercel AI SDK?

Install ai and @ai-sdk/mcp. Use createMCPClient with an HTTP transport pointing to your server URL. Call mcpClient.tools() and pass the result to your streamText function.

Q: Can Vercel AI SDK stream data from the getpetroleumtrade tool?

Yes. When your agent calls getpetroleumtrade to check import and export movements, the SDK streams the text response to your frontend in real-time. You never force the user to wait for the full trade balance to calculate.

Q: How do I handle authentication for EIA Petroleum — Oil Market Intelligence in Vercel AI SDK?

You configure an authProvider when initializing the MCP client. This passes your single endpoint token to the managed Vinkius server, handling the connection before the agent requests any refinery data.

Build live oil market dashboards in React. Stream EIA prices and production data directly into your UI using Vercel AI SDK.

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Connect EIA Petroleum — Oil Market Intelligence MCP to Vercel AI SDK

Create your Vinkius account to connect EIA Petroleum — Oil Market Intelligence to Vercel AI 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 Vercel AI SDK

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Stream WTI and Brent Prices via Vercel AI SDK

The `get_petroleum_prices` tool pulls live WTI, Brent, gasoline, and diesel retail figures straight into your application. When a user asks for current heating oil rates, your agent fetches the exact frequency and area data without a loading spinner. The Vercel AI SDK streams the numbers right into your Next.js frontend as the model processes them. You also get the weekly petroleum status report through `get_petroleum_summary`. This means your UI can instantly render supply and demand balances alongside production and import volumes. You don't wait for a massive JSON payload to resolve before showing the user the market equilibrium.

Render Strategic Reserve and Import Data

Use the `get_petroleum_stocks` tool to expose commercial inventories and Strategic Petroleum Reserve levels. Your AI client grabs this data and feeds it into your Svelte or Vue charts. Users see the exact barrel counts and historical stock movements the moment the API returns the figures. Pair this with `get_crude_imports` to break down incoming crude by country, company, and grade. Your application can map out exactly where domestic refineries are sourcing their heavy or light crude. The Edge-compatible setup means these queries run close to your users, keeping latency low.

Track U.S. Output and Refinery Utilization

The `get_crude_production` tool tracks U.S. crude oil production and reserves data. Your frontend components can display domestic output trends as text or structured data blocks. If a user wants to know how much oil the Permian basin is pumping, the agent retrieves the exact metrics. You can then cross-reference those production numbers with `get_refinery_operations` and `get_petroleum_consumption`. This lets your UI show refinery capacity, utilization rates, and sector-specific sales. The developer builds a live window into the domestic oil supply chain, fully powered by this MCP server.

Setup guide

Set up EIA Petroleum — Oil Market Intelligence MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all EIA Petroleum — Oil Market Intelligence tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent EIA Petroleum — Oil Market Intelligence transactions",
});

console.log(text);
await mcpClient.close();

Get your connection token →

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Common questions about EIA Petroleum — Oil Market Intelligence MCP in Vercel AI SDK

Install `ai` and `@ai-sdk/mcp`. Use `createMCPClient` with an HTTP transport pointing to your server URL. Call `mcpClient.tools()` and pass the result to your `streamText` function.

Yes. When your agent calls `get_petroleum_trade` to check import and export movements, the SDK streams the text response to your frontend in real-time. You never force the user to wait for the full trade balance to calculate.

It works perfectly on the Edge. The MCP client uses standard HTTP transports, so you can deploy your oil market dashboard to Vercel Edge Functions without compatibility issues.

You configure an `authProvider` when initializing the MCP client. This passes your single endpoint token to the managed Vinkius server, handling the connection before the agent requests any refinery data.

This server exclusively handles public macroeconomic and commodity data like WTI crude prices, refinery utilization rates, and SPR inventory levels. It does not touch PII or private user records. The V8 Isolate Sandbox destroys the connection state immediately after the Vercel AI SDK finishes streaming the response.

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