NREL Energy Data MCP. Model site viability with solar, geo, and utility data.
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NREL Energy Data gives your AI agent access to the National Renewable Energy Laboratory's massive dataset. Use it to track alternative fuel stations (Electric, Hydrogen, E85) globally; calculate solar production using PVWatts® estimates; get detailed solar radiation data (GHI/DNI); and retrieve current utility rates and service areas.
It’s a single source for planning sustainable energy projects.
What your AI agents can do
Get geothermal resource
Checks the geothermal resource potential at a specific set of coordinates.
Get nearest stations
Finds and lists alternative fuel stations closest to a provided address or location.
Get pvwatts estimates
Calculates the projected annual energy output for a photovoltaic system at given coordinates and size.
Find nearby or list all alternative fuel stations (Electric, Hydrogen, E85) using geographical coordinates.
Calculate the potential annual AC energy production of a photovoltaic system based on its size and location.
Check geothermal or solar radiation data (GHI, DNI) for any given geographic coordinate to assess resource viability.
Identify which utility companies serve a specific zip code and what their average electricity rates are.
Get comprehensive details on a known fuel station using its unique identifier or list all available stations.
Ask AI about this MCP
Supported MCP Clients
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NREL Energy Data MCP Server: 10 Tools for Energy Planning
Use these tools to query geothermal potential, calculate solar yields, map fuel stations, and retrieve comprehensive utility service data.
019d75dfget geothermal resource
Checks the geothermal resource potential at a specific set of coordinates.
019d75dfget nearest stations
Finds and lists alternative fuel stations closest to a provided address or location.
019d75dfget pvwatts estimates
Calculates the projected annual energy output for a photovoltaic system at given coordinates and size.
019d75dfget solar data query
Checks if specific solar datasets are available for a requested time period or area.
019d75dfget solar resource
Retrieves detailed solar radiation metrics (GHI, DNI) for any given geographic coordinates.
019d75dfget station details
Fetches all metadata and specific operational details about a known fuel station using its unique ID.
019d75dfget utility companies
Identifies which utility companies service a specified local area or zip code.
019d75dfget utility rates
Retrieves the average electricity rates for residential, commercial, and industrial use in an area.
019d75dflist alt fuel stations
Lists all alternative fuel stations recorded in the NREL database without needing coordinates.
019d75dflist transportation incentives
Provides a list of federal and state incentives related to alternative fuels and vehicles.
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What you can do with this MCP connector
NREL Energy Data gives your AI agent access to the National Renewable Energy Laboratory's massive energy dataset. You use this server when you need hard data to plan sustainable projects, whether it’s setting up solar farms or figuring out where to put a hydrogen station. It pulls from deep archives of alternative fuel and resource information.
Mapping Out Fuel Infrastructure
You can track alternative fuels—Electric, Hydrogen, and E85 sites—everywhere. Start by running list_alt_fuel_stations if you just want to see every single station recorded in the NREL database; it'll dump a complete list for you. If you have an address or specific coordinates, use get_nearest_stations, and your agent will find all the fuel spots closest to that point.
Once you pinpoint a facility using its unique ID, run get_station_details to pull every single piece of metadata about it—you'll get operational specifics and comprehensive details.
Calculating Solar Power Potential
Want to know how much energy your solar array is gonna make? Use get_pvwatts_estimates. You input the system size and the coordinates, and it calculates the projected annual AC energy output. It's a straight-up estimate of potential power. If you need more raw resource data—the stuff that feeds into those estimates—use get_solar_resource to grab detailed solar radiation metrics like Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) for any spot on the map.
You should check if the specific datasets you're looking at are even available first; run get_solar_data_query with your desired time period or area to make sure the data exists.
Utility Service and Resource Analysis
To figure out where a project can actually get hooked up, you gotta know the utility companies. Run get_utility_companies on a specific zip code or local area, and your agent will identify which providers service that location. After knowing who services it, you can run get_utility_rates. This tool retrieves the average electricity costs for three separate uses: residential, commercial, and industrial use in that exact area.
If you're looking at deep geological potential, you can check geothermal resources using get_geothermal_resource with coordinates to assess viability.
Planning & Incentives
When it comes to planning a whole project, remember the incentives. Use list_transportation_incentives to get a list of federal and state programs for alternative fuels and vehicles. These are crucial details you need when pitching the project. It's really a single source for figuring out resource availability—from fuel spots and solar irradiance to local utility rates and geothermal potential.
How NREL Energy Data MCP Works
- 1 First, subscribe to the server and acquire your NREL Developer API Key (you get this for free at developer.nrel.gov/signup).
- 2 Second, pass the required parameters—like coordinates or a zip code—to your AI client, asking it to run an analysis.
- 3 Finally, the agent executes the necessary tool calls and returns structured data: solar yields, rate tables, or station lists.
The bottom line is you get accurate, actionable energy planning data without having to visit multiple government websites.
Who Is NREL Energy Data MCP For?
Anyone dealing with complex infrastructure planning—from sustainability consultants reporting to clients, to fleet managers mapping out EV routes. If your job requires knowing where the next charging station is or how much solar power a site can generate, you need this.
Automates client reports by running get_pvwatts_estimates and collecting utility rates via get_utility_rates for multiple potential sites.
Quickly gathers solar radiation data (get_solar_resource) and geothermal resource reports for environmental impact studies across large regions.
Maps out optimal EV routes by calling get_nearest_stations to ensure charging infrastructure is available along the path.
What Changes When You Connect
- Automate feasibility reports. Instead of manually checking multiple government sites for rates and yields, you run
get_utility_ratescombined withget_pvwatts_estimatesto build a cost-benefit analysis in minutes. - Map infrastructure gaps instantly. Use
get_nearest_stationsto see exactly where charging stations are relative to a route, ensuring your client's fleet never gets stranded—and list all known sites withlist_alt_fuel_stationsfor comparison. - Deep dive into resource quality. Need to know if a site is worth solar power? Run
get_solar_resourcefirst; it provides GHI and DNI metrics, which are better inputs than just looking at a general map. - Cover the full energy spectrum. This server doesn't stop at solar. You can check geothermal potential (
get_geothermal_resource) or confirm utility service areas usingget_utility_companies, giving you a holistic view of site readiness. - Keep your project legally sound. Access incentive data via
list_transportation_incentivesand retrieve state laws to make sure your recommendations are both technically viable and financially supported.
Real-World Use Cases
Planning a new EV depot route
The client needs to run an electric bus route through three different towns. Instead of calling the local transit authority for each one, you use your agent to call get_nearest_stations repeatedly along the proposed path and then verify rates using get_utility_rates. This immediately flags service gaps or high operational costs.
Evaluating a commercial site for solar power
A client owns an empty lot (coordinates provided) and wants to know the maximum energy output. You run get_solar_resource first to validate GHI/DNI, then use that data point in get_pvwatts_estimates to provide a solid, quantified yield projection for their investment pitch.
Assessing mixed-source energy potential
The project involves a remote industrial site. You need to know if they can use solar or geothermal power. You run get_solar_resource and then immediately follow up with get_geothermal_resource. The agent compares the two outputs, giving you immediate options for alternative energy sources.
Quickly verifying utility serviceability
You get a potential address from a real estate listing. Before wasting time on site visits, you use get_utility_companies and get_utility_rates to confirm two things: 1) Does the utility actually serve this zip code? 2) What are their current rates for industrial power?
The Tradeoffs
Only checking solar data.
Someone thinks that if they run get_pvwatts_estimates once, they have all the energy data needed. They ignore utility rates or alternative fuel options entirely.
→
Always check for multiple inputs. If you estimate solar yield, follow up by calling get_utility_rates and then checking list_alt_fuel_stations. This ensures you account for both cost and diverse power sources.
Using vague location data.
Just typing 'near a big city' into the prompt without coordinates or a zip code. The agent will fail because most tools require precise geographic input to function correctly.
→
Be specific. Use either full coordinates (for get_solar_resource or get_geothermal_resource) or a valid zip code (for utility lookups like get_utility_companies). Don't assume the location context.
Confusing resource data with cost.
Reading high solar yield numbers from get_pvwatts_estimates and assuming the project is immediately profitable. The user forgets to check local utility rates or necessary incentives.
→
Treat every output as a data point, not a conclusion. Always cross-reference potential generation with current costs by running get_utility_rates and checking for available funding via list_transportation_incentives.
When It Fits, When It Doesn't
Use this server if your job requires comparing technical energy potential (solar, geothermal) against local economic realities (utility rates, fuel availability). This is the core value: synthesizing yield data with cost data. Don't use it if you only need to find a gas station—that’s too simple for these tools. Conversely, don't rely on this server just because it has solar tools; remember that get_pvwatts_estimates gives potential output, not guaranteed revenue. You must always cross-reference potential yield with existing infrastructure via get_utility_companies, and confirm the economics using get_utility_rates. If you only need to know what kind of electricity is available—and nothing about cost or capacity—other simpler GIS tools might suffice. But if the goal is a full, actionable energy plan, this toolset forces you through the necessary technical checks.
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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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Pinpointing energy infrastructure shouldn't require jumping between five different government websites.
Today, to figure out if an area can support a new fleet of electric vehicles, someone has to start by looking up the general service area using one site. Then they have to hop over to another site just for EV charger maps. If that doesn't work, they might spend hours manually finding the local utility rates on yet a third portal.
With NREL Energy Data, your AI agent handles this whole mess in two prompts. You ask for 'EV charging and power costs in 90210,' and it uses `get_utility_companies`, locates facilities via `get_nearest_stations`, and pulls the rates using `get_utility_rates`. You get a single, integrated answer.
NREL Energy Data MCP Server: Access utility rate data with `get_utility_rates`.
Before this server, figuring out the true cost of running a facility meant calling or manually checking state-specific tariff sheets for residential vs. industrial rates—a tedious process prone to outdated information and calculation errors.
Now, you just ask your agent for 'average electricity rates in downtown Dallas.' It executes `get_utility_rates` and gives you the precise breakdown: what commercial pays versus what a home pays. It's definitive.
Common Questions About NREL Energy Data MCP
How do I find all alternative fuel stations using list_alt_fuel_stations? +
You simply call list_alt_fuel_stations with no parameters. The agent returns a database listing of every known station, regardless of your specific coordinates or current location.
Is get_pvwatts_estimates used for actual installation planning? +
It is designed to estimate potential annual AC energy production using PVWatts® models. Remember this gives you a projection; always cross-reference the result with local utility rates via get_utility_rates to account for costs.
What's the difference between get_solar_resource and get_pvwatts_estimates? +
get_solar_resource provides raw data points like Global Horizontal Irradiance (GHI) or Direct Normal Irradiance (DNI) for a location. get_pvwatts_estimates takes those inputs, along with system size, and calculates the resulting energy yield.
Do I need coordinates to use get_utility_companies? +
No, you can often specify a zip code for utility lookups. Using a zip code is usually sufficient to identify local companies that serve that area.
How do I handle authentication when using get_station_details? +
You must provide an NREL Developer API Key to access this server. Your AI client needs that key passed through the connection settings. Without it, any tool call will fail with an authorization error.
What happens if I use get_utility_rates for a zip code with no recorded data? +
The agent handles missing inputs gracefully. Instead of failing, it returns a clear 'No Data Found' message. It often suggests checking adjacent codes or expanding your search area.
Is get_geothermal_resource compatible with different AI clients? +
Yes, the tool works across all MCP-compatible agents (Claude, Cursor, etc.). The function only requires latitude and longitude inputs; the client manages the execution environment.
Can I retrieve full metadata using get_station_details? +
Absolutely. This tool fetches comprehensive data beyond just location and type. It retrieves complete metadata, station descriptions, unique IDs, and any operational details needed for deep analysis.
Is the NREL API Key free? +
Yes! You can sign up for a free API key at https://developer.nrel.gov/signup/. Standard limits apply (1,000 requests per hour).
What is PVWatts used for? +
PVWatts estimates the energy production and cost of energy of grid-connected photovoltaic (PV) energy systems throughout the world.
Can I search for EV charging stations? +
Yes! EV charging stations are included in the Alternative Fuel Stations dataset. Use the get_nearest_stations tool to find them near a specific location.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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