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

Q: How can I analyze electricity generation with U.S. EIA Energy Data using CrewAI?

Create a crew where the researcher agent uses listelectricitygeneration to gather all retail sales data, and the analyst agent summarizes trends from that dataset for you.

Q: Does CrewAI support listing natural gas production with U.S. EIA Energy Data?

Absolutely. The crew can utilize listnaturalgasproduction to gather supply and distribution data, which a specialized agent can then use to model future resource availability.

Q: What are the steps for querying U.S. EIA Energy Data with CrewAI?

Start by giving your crew access to geteiaapimetadata. This allows the agents to first verify connection credentials and available tools before starting any major analysis.

Q: Can I compare fuel prices using U.S. EIA Energy Data with CrewAI?

Yes. You can assign one agent to fetch listpetroleumprices while another fetches listregionalfuelprices. The crew then compares the two datasets, identifying regional price discrepancies.

Build autonomous operations analyzing U.S. EIA Energy Data using CrewAI.

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Connect U.S. EIA Energy Data MCP to CrewAI

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

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Automate energy resource comparison.

Run a crew where one agent uses `list_natural_gas_production` to gather supply metrics, and another agent uses `list_coal_production` to get coal data. The third agent then synthesizes a comparative report based on the shared memory. This multi-agent setup lets you move beyond simple API calls; it allows specialized roles—researcher, analyst, reporter—to collaborate autonomously.

Monitor energy market status via MCP Server

Set up a monitor agent that runs `quick_us_energy_audit` periodically. If the audit detects an anomaly or gap in the data, a moderator agent is automatically triggered to escalate the issue or call `get_eia_api_metadata` for diagnostic details. This level of autonomous operation means your system watches itself and takes action when external energy metrics look off.

Get comprehensive fuel data sets.

You can have agents sequentially call `list_energy_categories`, then `list_renewable_energy_stats`, and finally `list_regional_fuel_prices`. The crew ensures that the output of one step is passed directly as context to the next, building a complete picture. It's about structured data pipelines. You don't just get lists; you get an organized report built by specialized roles working together.

Setup guide

Set up U.S. EIA Energy Data MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke U.S. EIA Energy Data tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="U.S. EIA Energy Data Analyst",
    goal="Access and analyze U.S. EIA Energy Data data via MCP.",
    backstory="Expert analyst with direct U.S. EIA Energy Data access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent U.S. EIA Energy Data transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="U.S. EIA Energy Data Analyst",
        goal="Access and analyze U.S. EIA Energy Data data via MCP.",
        backstory="Expert analyst with direct U.S. EIA Energy Data access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent U.S. EIA Energy Data transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

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 CrewAI

Create a crew where the researcher agent uses `list_electricity_generation` to gather all retail sales data, and the analyst agent summarizes trends from that dataset for you.

Absolutely. The crew can utilize `list_natural_gas_production` to gather supply and distribution data, which a specialized agent can then use to model future resource availability.

Start by giving your crew access to `get_eia_api_metadata`. This allows the agents to first verify connection credentials and available tools before starting any major analysis.

Yes. You can assign one agent to fetch `list_petroleum_prices` while another fetches `list_regional_fuel_prices`. The crew then compares the two datasets, identifying regional price discrepancies.

The server handles structured energy statistics and pricing data, like renewable generation metrics and gas supply numbers. It's all read-only, aggregated information.

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