How to Use the NREL Energy Data MCP in OpenAI Agents SDK

Plug NREL Energy Data into your OpenAI Agents SDK production pipeline to automate site assessments and infrastructure planning.

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Connect NREL Energy Data MCP to OpenAI Agents SDK

Create your Vinkius account to connect NREL Energy Data to OpenAI Agents 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 NREL Energy Data with OpenAI Agents SDK

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Claude

Perplexity

Automated energy site scouting

Your agent identifies viable locations by querying `list_alt_fuel_stations` and `get_station_details`. It filters through regional data to pinpoint exactly where your infrastructure fits best. This process happens inside your execution loop. You get structured data ready for your agent's decision logic without manual lookups.

Grid and utility cost analysis

Connect your agent to `get_utility_rates` and `get_utility_companies` to calculate operating expenses in real-time. The agent pulls current figures to compare potential site profitability. These calls integrate directly into your agent's tool set. You avoid hard-coded estimates and rely on live data for every simulation.

Solar production forecasting

Run `get_pvwatts_estimates` or `get_solar_resource` to gauge potential output for specific coordinates. Your agent evaluates renewable capacity before suggesting a site for development. This MCP Server provides the raw numbers your agent needs to justify its recommendations. It turns vague site goals into concrete energy projections.

Setup guide

Set up NREL Energy Data MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all NREL Energy Data tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives NREL Energy Data tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate NREL Energy Data tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="NREL Energy Data Agent",
            instructions="You have access to NREL Energy Data tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about NREL Energy Data MCP in OpenAI Agents SDK

You instantiate the server connection and pass it to your agent constructor. The SDK handles tool discovery automatically, letting your agent call the functions immediately.

Yes. Every tool output undergoes your defined validation logic. If a response from the server doesn't match your expected schema, the guardrails catch it before the agent acts.

You should use the caching features provided in the SDK. By enabling tool list caching, you keep performance high while the agent processes multiple site assessments.

The connection relies on your endpoint token. It creates a secure tunnel between your agent and the server, ensuring only authenticated traffic reaches the data source.

The server only processes the specific coordinates or utility identifiers you send. No telemetry or proprietary site data is stored by the server provider.

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