How to Use the NREL Energy Data MCP in CrewAI

Q: What geothermal metrics can my crew analyze?

Your agents can use getgeothermalresource to retrieve temperature and depth data for any location. This lets your crew evaluate geothermal viability alongside solar and wind options.

Deploy teams of specialized agents with CrewAI to analyze NREL grids and utility rates autonomously.

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Connect NREL Energy Data MCP to CrewAI

Create your Vinkius account to connect NREL 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 NREL Energy Data with CrewAI

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Collaborative Solar Planning with CrewAI

Estimating solar output requires `get_pvwatts_estimates` to model system performance over a year. In a CrewAI setup, one agent can generate these estimates while another analyzes the financial viability. This MCP server lets your agent team share data directly. The analyst agent takes the output from the solar tool and immediately starts calculating payback periods.

Analyze Grid Providers Autonomously

Identifying regional power companies uses `get_utility_companies` to map service providers to local coordinates. Your research agent runs this scan first to establish the local utility market. Next, a financial agent can call `get_utility_rates` to pull average electricity costs. Working together via this MCP protocol, the crew builds a complete profile of regional energy costs without human input.

Plan Alternative Fuel Infrastructure

Mapping out fleet refueling relies on `list_alt_fuel_stations` to identify existing charging and fueling infrastructure. A logistics agent can scan this list to find gaps in regional coverage. Meanwhile, a policy agent can run `list_transportation_incentives` to find grants that fund new stations. The crew combines these findings into a unified transition plan.

Setup guide

Set up NREL 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 NREL Energy Data tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent NREL Energy Data transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

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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="NREL Energy Data Analyst",
        goal="Access and analyze NREL Energy Data data via MCP.",
        backstory="Expert analyst with direct NREL Energy Data access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent NREL 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 NREL. 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 NREL Energy Data MCP in CrewAI

Pass the Vinkius MCP server URL directly into your agent's configuration. You can restrict tools so only your analyst agent can access solar estimators while the researcher finds fuel stations.

Yes, CrewAI's shared memory allows agents to pass tool outputs to each other. If one agent fetches details with `get_station_details`, the next agent can immediately use that data.

The MCP server handles concurrent requests through our scalable infrastructure. Your crew can run multiple tool calls simultaneously without hitting local bottleneck blocks.

Your agents can use `get_geothermal_resource` to retrieve temperature and depth data for any location. This lets your crew evaluate geothermal viability alongside solar and wind options.

Location coordinates and site queries are processed entirely in memory within our secure MCP isolates. Vinkius does not save or log your geographic inputs, keeping your site planning confidential.

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