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

Q: How do I connect EIA Petroleum — Oil Market Intelligence to my LlamaIndex knowledge base?

You use the McpToolSpec to get the list of tools and convert them for your LlamaIndex agent. The agent can then call the tools, and you can configure LlamaIndex to automatically index the results into your vector store.

Ground your LlamaIndex RAG application in live oil market intelligence.

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Connect EIA Petroleum — Oil Market Intelligence MCP to LlamaIndex

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

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Turn API Calls into Knowledge

LlamaIndex doesn't just call a tool, it learns from it. When your agent uses `get_petroleum_stocks`, the current SPR level is automatically indexed and stored. The output of the API call becomes part of a searchable memory. You can then query the past. Ask, 'What were commercial crude inventories last week when WTI hit $90?' Your agent retrieves the answer from its own indexed history of tool calls, giving you grounded facts without re-running queries.

Ground Answers in Hard Data

Build a RAG application that answers questions with citations from the real world. When you ask about refinery capacity, your LlamaIndex agent can pull data from `get_refinery_operations` and embed the actual numbers in its response. This is how you stop hallucinations. The agent's understanding is built directly from the ground truth of the EIA data feed. It knows production figures from `get_crude_production` and trade flows from `get_petroleum_trade` because it has the data.

A Queryable LlamaIndex Data Source

This MCP Server adds a live data feed directly into your query engine. Your LlamaIndex app can now synthesize information from your static documents and real-time market data from the EIA in a single query. An agent analyzing news articles about OPEC can now cross-reference claims against live import data from `get_crude_imports`. It's the combination of your knowledge base and live context that gives you an edge.

Setup guide

Set up EIA Petroleum — Oil Market Intelligence MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all EIA Petroleum — Oil Market Intelligence MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to EIA Petroleum — Oil Market Intelligence tools.",
)
response = await agent.run("List recent EIA Petroleum — Oil Market Intelligence data")

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

You use the `McpToolSpec` to get the list of tools and convert them for your LlamaIndex agent. The agent can then call the tools, and you can configure LlamaIndex to automatically index the results into your vector store.

Yes, that's the point of using LlamaIndex. By indexing the tool outputs, you create a searchable knowledge base of past market conditions. You can query this history just like any other document.

Indexing creates a memory. It lets you find relationships in data over time and grounds your agent's responses in facts it has already verified, which is much faster and more reliable than making live calls for every query.

Yes, LlamaIndex needs a vector database (like Chroma, Pinecone, or others) to store and index the results from the EIA tool calls. This server provides the data; LlamaIndex makes it searchable.

LlamaIndex will index the results of your queries, which is public U.S. petroleum market data. Your connection itself is secured through the Vinkius platform, which handles authentication without ever storing your private keys on our end.

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