How to Use the U.S. EIA Energy Data MCP in LlamaIndex

Q: How do I access live U.S. EIA Energy Data using LlamaIndex?

You pass the tool definitions (like getenergyseriesdata) to your FunctionAgent. The agent runs the query, and the resulting data is then automatically added to your searchable knowledge index.

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Connect U.S. EIA Energy Data MCP to LlamaIndex

Create your Vinkius account to connect U.S. EIA Energy Data 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 U.S. EIA Energy Data with LlamaIndex

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Perplexity

Indexing Energy Trends

LlamaIndex turns raw API output into a searchable knowledge base, so you don't have to re-query the same data repeatedly. For example, after calling `list_electricity_generation`, the results become indexed. You can later ask, 'What did electricity generation look like in Q2?' and get an answer grounded in that stored data.

Querying Price History

Instead of just getting a single snapshot, you index historical price movements. Run `list_petroleum_prices` once, then query the resulting knowledge base weeks later to find specific price fluctuations without making another API call.

Combining Data Sources for RAG

You can combine live data with documents using a unified index. Indexing results from `list_regional_fuel_prices` alongside internal reports means your agent answers questions based on both the real-time API call and static context.

Setup guide

Set up U.S. EIA Energy Data 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 U.S. EIA Energy Data 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 U.S. EIA Energy Data tools.",
)
response = await agent.run("List recent U.S. EIA Energy Data data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by U.S. EIA Energy Data. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about U.S. EIA Energy Data MCP in LlamaIndex

LlamaIndex doesn't just run a query; it indexes the output from tools like `list_natural_gas_production`. This means you can perform semantic searches against the data, asking complex questions that traditional database lookups would miss.

Yes. Because the tool output becomes part of a vector store, you can query past sessions or configurations and get answers directly grounded in actual API results from tools like `list_coal_production`.

The server provides time-series metrics, including electricity generation, renewable statistics via `list_renewable_energy_stats`, and detailed fuel price points that are all indexed for later retrieval.

The client supports inclusion of resources. You control what gets added to the index, allowing you to mix sensitive internal documents with public API results from this MCP Server.

You pass the tool definitions (like `get_energy_series_data`) to your FunctionAgent. The agent runs the query, and the resulting data is then automatically added to your searchable knowledge index.

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