OpenEI MCP. Model energy costs using US utility rates.
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OpenEI lets your agent query the National Utility Rate Database for US electricity rates. You can check tariffs by street address or GPS coordinates and segment results by residential, commercial, or industrial use.
Use it to model energy costs, analyze solar ROI, or compare utility charges across different locations.
What your AI agents can do
Get commercial rates
Gets all available commercial tariffs (general service, large power, time-of-use) for a location using lat/lon or address.
Get industrial rates
Retrieves industrial electricity rates, which are useful for heavy manufacturing cost analysis and load forecasting.
Get rate detail
Returns the complete rate structure—including fixed charges, demand charges, and seasonal variations—for a specific utility tariff ID.
Find all available tariffs—residential, commercial, and industrial—by providing a street address or GPS coordinates.
Pull dedicated rate structures for commercial operations (get_commercial_rates) or heavy manufacturing facilities (get_industrial_rates).
Get the full cost breakdown of any identified rate ID, including demand charges and time-of-use periods.
Search for specific power companies or list all utilities serving an area to map service territories.
Get rate quotes tailored for calculating ROI and net metering, perfect for site proposals.
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OpenEI MCP Server: 10 Tools for Energy Rate Analysis
Use these ten tools to find, compare, and deeply analyze utility rates across all major sectors (residential, commercial, industrial) by location.
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Start using OpenEI on Vinkius019d8466get commercial rates
Gets all available commercial tariffs (general service, large power, time-of-use) for a location using lat/lon or address.
019d8466get industrial rates
Retrieves industrial electricity rates, which are useful for heavy manufacturing cost analysis and load forecasting.
019d8466get rate detail
Returns the complete rate structure—including fixed charges, demand charges, and seasonal variations—for a specific utility tariff ID.
019d8466get rates by address
Takes a street address as input to identify the serving utility and return all applicable rates at that exact location.
019d8466get rates by coordinates
Accepts GPS coordinates to automatically find and list available residential, commercial, and industrial tariffs for that spot.
019d8466get residential rates
Retrieves all home electricity tariffs, covering tiered rates, time-of-use plans, and EV charging options.
019d8466get utility detail
Provides detailed info on a utility company, including its service territory, contact details, and generation mix.
019d8466get utility rates
Finds applicable rates for any location (by address or coordinates) and allows filtering by rate sector: residential, commercial, or industrial.
019d8466list utilities
Lists utility companies in the database, allowing you to filter results by state, country, or company name.
019d8466search utilities by name
Finds matching utility companies and their IDs when you only know part of the business name.
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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.
Figuring out utility costs used to feel like a scavenger hunt through PDFs and outdated rate schedules.
Before tools like OpenEI, you had to manually cross-reference addresses with local utility websites. You'd spend hours downloading PDF tariff sheets for residential rates, commercial tariffs, *and* industrial charges—all just to figure out if solar ROI was even possible on a given site. Then you'd have to piece together the demand charge rules and seasonal variations by comparing documents.
Now, OpenEI lets your agent handle that whole process in a single query. You give it the address; your AI client pulls the full rate structure. It separates residential from commercial rates, flags time-of-use periods, and gives you clean data points for cost modeling—no more hunting through PDFs.
OpenEI MCP Server: Use `get_rate_detail` to get every charge breakdown.
The most time-consuming part of energy analysis is understanding the 'fine print.' Utility bills aren't simple kWh charges; they include fixed fees, minimum service charges, and complex demand factors. If you only look at basic rates, your entire cost projection fails because you miss these structural components.
When you use `get_rate_detail`, OpenEI surfaces every single component of the tariff: energy charges, minimums, seasonal shifts, and more. You get a complete financial picture that lets you model costs accurately, eliminating guesswork from day one.
What you can do with this MCP connector
You're dealing with US electricity rates? You need OpenEI. This MCP Server connects your agent straight to the National Utility Rate Database—it’s where all the official utility tariffs live. Forget digging through PDFs or outdated spreadsheets; you just tell your AI client what you need, and it handles the whole complicated rate lookup process.
Finding Rates by Location
If you know exactly where you are, you don't gotta guess. You can use get_rates_by_address to input a simple street address; the server figures out which utility serves that location and lists all applicable rates right there. If you prefer GPS coordinates, just feed those into get_rates_by_coordinates. This gives your agent an instant list of residential, commercial, and industrial tariffs for that exact spot.
You can also run a broader check using get_utility_rates, which lets you filter by rate sector—residential, commercial, or industrial—if you just have the general area.
Deep Diving into Specific Sectors
You'll pull dedicated structures when you need to model specific operations. For homes, you use get_residential_rates. This tool pulls all home electricity tariffs, covering everything from tiered rate plans and time-of-use schedules to rates designed for EV charging options. If you’re working on a business site, the get_commercial_rates function gives you access to general service, large power, and time-of-use commercial tariffs based on location or address.
For heavy manufacturing analysis and load forecasting, you'll grab industrial electricity rates using get_industrial_rates. These are critical for understanding high-consumption cost centers.
Utility Research and Mapping Service Areas
You might not know who serves the site yet. You can start by listing all available utility companies in a region with list_utilities, letting you filter results by state, country, or company name to map out service territories. If you only catch part of a business name, no sweat—you use search_utilities_by_name to find the matching utility and its ID number.
Once you have the company ID, get_utility_detail gives you the full rundown: their service territory boundaries, contact info, and even what mix of power sources they’re using. You'll also pull specific details on a single tariff structure using get_rate_detail, which returns the complete cost breakdown—that means fixed charges, demand charges, and how seasonal variations impact the bill.
Modeling Energy Costs and Feasibility Data
When you run these rates through your agent, you're not just getting a list of numbers. You're building models. The data allows you to analyze complex rate structures like time-of-use periods and demand charges for accurate cost modeling. For site proposals or solar ROI calculations, the available tariffs let you get quotes tailored specifically for net metering and energy efficiency analysis.
By combining location searches with sector-specific rates, you'll walk away knowing exactly what a client's utility costs are across residential, commercial, and industrial uses anywhere in the country.
019d8466-ad3e-724c-a9c7-2c7dde0a1e53 
How OpenEI MCP Works
- 1 First, tell your agent where you need rates. Give it an address (e.g., '123 Main St') or coordinates (lat/lon).
- 2 Next, specify what kind of rate structure you want: residential, commercial, or industrial. The tool finds the serving utility and returns initial options.
- 3 Finally, if you need details like demand charges or time-of-use periods, ask your agent to run a deep dive using
get_rate_detailon the specific tariff ID.
The bottom line is: OpenEI lets your AI client pull complex, location-specific energy cost data into plain conversation.
Who Is OpenEI MCP For?
Solar installers and energy consultants are the primary users. They need accurate rate structures to give clients real quotes. Facility managers use it when planning site selection or running budget models, eliminating guesswork from utility bills.
Runs full cost modeling simulations for clients, comparing residential vs. commercial tariffs across different geographic points.
Gets instant rate quotes at a client's address to calculate ROI and net metering details before writing a proposal.
Compares utility rates across multiple potential sites for new office spaces or manufacturing plants, focusing on industrial demand charges.
What Changes When You Connect
- Stop guessing on site bids. Use
get_rates_by_addressto get instant, accurate rate quotes for solar ROI calculations right from the client's street address. - Understand complex industrial billing.
get_industrial_ratesprovides critical data points like demand charges and power factor adjustments needed for heavy manufacturing models. - Compare rates across sectors effortlessly. Instead of running separate queries, use
get_utility_ratesto pull residential, commercial, and industrial tariffs from one location lookup. - Get the full story on a tariff. When you nail down a rate ID, always run
get_rate_detail. This tool gives you the complete breakdown—fixed charges, seasonal shifts, everything. - Research without limits. Use
list_utilitiesorsearch_utilities_by_nameto map out which utilities actually serve a region before running cost models.
Real-World Use Cases
Calculating ROI for a new commercial client.
A facility manager needs to bid on a warehouse project. They use get_rates_by_address first, confirming the utility and general rates. Then, they call get_commercial_rates and follow up with get_rate_detail to nail down demand charges for their final proposal.
Mapping out a new solar installation territory.
A consultant needs to check 50 potential sites. Instead of manual lookups, they use the agent with get_rates_by_coordinates across all points. This quickly flags if any area uses specialized tariffs or requires deep investigation.
Understanding why a factory's bill is so high.
An operations engineer gets an unexpected utility bill. They feed the location data into get_utility_rates and then use get_rate_detail to see if they are being charged maximum demand rates or missing seasonal variations.
Comparing local residential options.
A homeowner wants to go solar but isn't sure about the best plan. They ask for get_residential_rates by their address, allowing them to compare tiered plans and time-of-use structures side-by-side.
The Tradeoffs
Treating all rates as one bucket
Asking the agent simply 'What are the electricity rates at this address?' This usually gives a basic summary, missing critical details like demand charges or commercial vs. residential separation.
→
Always start with get_utility_rates and specify the sector (e.g., Residential) or use get_commercial_rates if you know it’s for business use. This forces the model to get specific data.
Assuming one tool covers everything
Calling get_residential_rates and thinking that gives you commercial rates too. The tools are specialized, so mixing them up leads to incomplete cost models.
→
If the use case is for a business, run get_commercial_rates. If it's for a home, use get_residential_rates. Don’t try to combine them in one shot.
Ignoring the utility source
Just giving coordinates without first confirming which company services that spot. You might get generic rates, but they could be wrong for the actual provider.
→
Start by running get_utility_rates or using list_utilities to confirm the specific serving utility and its service territory before modeling costs.
When It Fits, When It Doesn't
Use OpenEI if your goal is cost analysis tied directly to US geography. Don't use this if you just need a general idea of electricity pricing; it requires an address or coordinates because rates change dramatically by utility and location.
If you are comparing different types of users (home vs. factory), run get_residential_rates and then separately run get_industrial_rates. If you only care about a single location, let the agent handle it using get_utility_rates first to narrow down the options before running specific sector tools like get_commercial_rates. Don’t use this if your data is from an international market; OpenEI is US-specific.
Common Questions About OpenEI MCP
How do I find rates for both residential and commercial use with OpenEI? +
You can run get_utility_rates and specify both sectors. Alternatively, you can run get_residential_rates and then separately call get_commercial_rates using the same location data.
Can I use OpenEI to check rates just by coordinates? +
Yes. Use get_rates_by_coordinates. This tool automatically identifies the serving utility and returns applicable tariffs for residential, commercial, and industrial uses at that GPS point.
What is the best way to get full tariff details using OpenEI? +
You must use get_rate_detail. This tool requires a specific rate ID you find first (e.g., from get_utility_rates) and then gives the exhaustive breakdown of all charges.
Does OpenEI cover multiple utilities in one search? +
Yes. You can use list_utilities or search_utilities_by_name first to map out which companies exist in a region, and then run specific rate lookups against them.
How do I properly authenticate OpenEI when connecting to my AI client? +
You must provide your unique OpenEI API Key during setup. Your agent uses this key to authorize every request, ensuring you access the National Utility Rate Database securely and keep usage tracked.
If I only know a general area, how can I use OpenEI to find potential utilities? +
Use the list_utilities tool. You can filter results by state or country to get a list of available companies and their service territories, which is useful for initial research.
What happens if I run OpenEI's rate tools with an invalid address? +
The server will return a specific geocoding error. Your AI client should catch this error and prompt you to try coordinates or search by utility name instead.
What data does the `get_utility_detail` tool provide beyond basic contact info? +
It returns comprehensive details, including the utility's service territory, owned generation resources, and a summary of all associated rates. This helps you understand their full operational scope.
How do I find electricity rates for my address? +
Use the get_rates_by_address tool with your full street address. The API will geocode your location and return all applicable utility rates (residential, commercial, industrial). For example, enter '1617 Cole Blvd, Golden, CO 80401' to see rates from Xcel Energy and other providers serving that area.
What's the difference between residential, commercial, and industrial rates? +
Residential rates (sector 1) are for homes and typically have simple tiered or time-of-use structures. Commercial rates (sector 2) serve businesses and include general service and large power tariffs with demand charges. Industrial rates (sector 3) are for heavy manufacturing with the lowest per-kWh costs but complex demand and power factor adjustments. Use the specific sector tools or filter with the sector parameter.
Can I get complete rate structures with time-of-use details? +
Yes. Set the detail parameter to 'full' when calling get_utility_rates or get_rate_detail. This returns the complete tariff structure including energyratestructure (time-of-use periods and seasonal blocks), demandratestructure, fixed charges, minimum charges, and tax adjustments. Essential for accurate solar ROI calculations and detailed energy cost modeling.
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