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PG&E Data Portals

PG&E Data Portals MCP for AI. Pinpoint local grid capacity and consumption trends.

Claude Claude
ChatGPT ChatGPT
Cursor Cursor
Gemini Gemini
Windsurf Windsurf
VS Code VS Code
JetBrains JetBrains
Vercel Vercel
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PG&E Data Portals MCP on Cursor AI Code EditorPG&E Data Portals MCP on Claude Desktop AppPG&E Data Portals MCP on OpenAI Agents SDKPG&E Data Portals MCP on Visual Studio CodePG&E Data Portals MCP on GitHub Copilot AI AgentPG&E Data Portals MCP on Google Gemini AIPG&E Data Portals MCP on Lovable AI DevelopmentPG&E Data Portals MCP on Mistral AI AgentsPG&E Data Portals MCP on Amazon AWS Bedrock

Connect to your AI in seconds.

PG&E Data Portals connects your AI client directly to PG&E's public energy datasets. Query electricity usage, solar generation capacity, and EV adoption trends by ZIP code and date range.

Use this server to programmatically analyze grid infrastructure data for planning, research, or market analysis.

What your AI can do

Query by date range

Retrieves records from any dataset that fall within specified start and end dates for trend analysis.

Query ev adoption

Retrieves electric vehicle registration counts, showing adoption rates for specific ZIP codes and years.

Query energy efficiency

Gets program results and savings amounts for energy efficiency initiatives, filtered by year and program type.

+ 7 more capabilities included
Catalog all available datasets

Lists every dataset PG&E tracks—including usage, solar, and grid data—so you know exactly where to look.

Inspect dataset structure

Retrieves the schema (columns and data types) for any specific PG&E dataset ID before running a query.

Query consumption by location and time

Gets electricity or gas usage records, filtered precisely by ZIP code and date range.

Analyze EV adoption trends

Retrieves electric vehicle registration counts and adoption rates for specific ZIP codes and years.

Assess grid infrastructure capacity

Accesses distribution circuit, substation data, and general grid capacity metrics by region.

Track solar energy production

Gathers solar generation statistics (like installed capacity or net energy metering) for a specific county or service area.

Included with Plan

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AI Agent

PG&E Data Portals MCP Server: 10 Tools for Energy Analytics

These tools give your AI client programmatic access to PG&E's public energy datasets, allowing you to query usage patterns, grid capacity, and adoption rates without manual API calls.

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Query By Date Range

Retrieves records from any dataset that fall within specified start and end dates for trend analysis.

Query Ev Adoption

Retrieves electric vehicle registration counts, showing adoption rates for specific...

Query Energy Efficiency

Gets program results and savings amounts for energy efficiency initiatives, filtered...

Query Energy Usage

Queries electricity or gas consumption data broken down by customer segment (e.g....

Get Dataset Schema

Shows the column names and data types for a specific PG&E dataset ID.

Query Grid Infrastructure

Queries data on distribution circuits, substations, and grid capacity by region or infrastructure type.

List All Datasets

Returns a list of all available datasets, including energy usage, solar, EV adoption, and grid infrastructure.

Query Dataset

Queries a specific PG&E dataset using key-value filters like zip code or region to...

Search Datasets

Searches the PG&E catalog using keywords to discover relevant datasets before...

Query Solar Generation

Gathers solar energy production statistics (capacity/production) for a specific...

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Claude AI

Claude AI

1

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Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

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3

Start a conversation

Open a new chat. The PG&E Data Portals integration is available immediately — no restart needed.

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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 connection provides 10 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Manually compiling regional utility data is a nightmare of spreadsheets and portals.

The old way means logging into the PG&E portal, finding the usage dashboard, downloading the CSV for residential users in ZIP 94102. Then you repeat that process—logging out, going to the separate Solar section, and downloading a second file for capacity data. You end up with two massive spreadsheets, manually matching dates, merging by region, and cross-checking fields just to answer one question.

With this MCP server, your AI client handles all those steps in the background. Instead of clicking through three different dashboards and exporting five separate files, you just ask: 'What was peak residential usage vs. installed solar capacity in 94102 for Q3?' The agent runs `query_energy_usage` and `query_solar_generation`, stitches the results together, and gives you a single answer.

PG&E Data Portals MCP Server: Querying Energy Usage

Before this tool, analyzing energy consumption meant running separate reports for every customer segment (industrial, commercial) and then manually calculating the aggregate. If you needed to look at usage trends across multiple years, you had to download a new report every time, leading to hours of tedious data manipulation in Excel.

Now, you specify 'commercial' and a date range with `query_energy_usage`. The agent handles the filtering and aggregation instantly. You get clean, structured records that let you focus on what the numbers mean—not how long it took to pull them.

What your AI can actually do with this

Listen up. This server hooks your agent right into PG&E’s public energy data portals. It's not some slick, vague dashboard; it gives you programmatic access to actual usage patterns, solar capacity figures, and grid infrastructure details. You don't gotta mess with manual downloads or weird web forms—your AI client just uses structured tools to get exactly what you need.

Finding Your Data

If you're not sure where the info lives, start by listing everything available using list_all_datasets; this shows every dataset PG&E tracks, from usage numbers to EV adoption rates. You can refine that search with search_datasets if you know a keyword but don't know the ID. Before running any query, you gotta check the structure; use get_dataset_schema by plugging in a specific PG&E dataset ID.

This tells you all the column names and data types, so you never waste time on a bad query.

Pulling General Data & Trends

You can pull records from any dataset that fall between two dates using query_by_date_range for trend analysis. For general querying when you know what you're looking for, run query_dataset, letting the tool filter by key-value pairs like a specific ZIP code or region.

Analyzing Energy Use and Efficiency

To check electricity or gas consumption data, use query_energy_usage. You can get records broken down specifically by customer segment—say, residential—and filtered precisely by ZIP code. If you're tracking energy efficiency programs, query_energy_efficiency gets you the program results and estimated savings amounts, letting you narrow it down by year or specific program type.

Tracking Renewables and Grid Health

For solar power, query_solar_generation collects statistics on production—like installed capacity or net energy metering—for a defined county or service area in a given year. If you need to assess the physical grid, query_grid_infrastructure pulls data on distribution circuits, substations, and overall grid capacity metrics, letting you filter by region or infrastructure type.

These tools let you map out where the power actually runs.

Mobility and Consumption Analysis

Need to track electric vehicles? query_ev_adoption retrieves EV registration counts, showing adoption rates for specific ZIP codes across years. For a comprehensive view of consumption, you can use query_energy_usage or look at solar metrics with query_solar_generation. These tools let you programmatically analyze everything from how many cars are electric to how much power the grid actually supports.

It's built for the guy who needs reliable, structured access to time-series energy data. You don't waste time on guesswork; your agent just pulls the numbers straight out.

Built · Hosted · Managed by Vinkius PG&E Data Portals MCP Server - Energy Usage & Grid Data
Server ID 019d75f1-e8ae-71fa-9d28-eeb4e18025be
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Questions you might have

How do I find all available PG&E datasets using list_all_datasets? +

Run list_all_datasets. This returns a catalog of every dataset, including energy usage, EV adoption, and grid infrastructure. It’s the best place to start when you don't know which data set you need.

What is the difference between query_dataset and get_dataset_schema? +

list_all_datasets gives you a list of available topics. get_dataset_schema drills down to show the column names, data types, and constraints for one specific dataset ID, letting you know exactly what fields you can filter on.

How do I query EV adoption rates by ZIP code? +

Use query_ev_adoption. You need to provide the 5-digit ZIP code and the specific year (YYYY format) in your prompt. This tool is designed specifically for this data type.

Can I analyze solar generation capacity trends using query_solar_generation? +

Yes, query_solar_generation handles that. You must specify the region (county name or service area) and the year to retrieve production statistics for trend analysis.

What filters can I use with query_energy_usage? +

query_energy_usage requires you to specify the ZIP code and a date range. You also select the customer segment (residential, commercial, industrial) you want to analyze.

What happens to my queries using `query_dataset` if I hit rate limits? +

You need an API key for high volume analysis. For sustained data querying, provide your PG&E Data Portals API Key during setup. This increases your allowed calls and keeps your complex analyses running without interruption.

What format must I use when calling `query_by_date_range`? +

The system requires the YYYY-MM-DD standard date format. Always pass both start and end dates using this structure to guarantee accurate filtering for any time-series comparison.

How do I narrow down my search results before running `query_dataset`? +

Use the keyword parameter when calling search_datasets. This filters the entire catalog based on your input, helping you find the exact dataset ID needed before you attempt to retrieve any data records.

What types of datasets are available? +

PG&E Data Portals offers: energy usage (electricity and gas by ZIP code), EV adoption (vehicle registrations), solar generation (capacity and production), energy efficiency programs (participation and savings), and grid infrastructure (distribution circuits, substations). Use search_datasets to discover all available datasets.

Is authentication required? +

No, the PG&E Data Portals API is publicly accessible without authentication. An API key is optional and only needed if you want higher rate limits for production use. Most queries work out of the box without any credentials.

Can I filter data by specific ZIP codes and date ranges? +

Yes! Most tools support zip_code, start_date, and end_date parameters. For example, query_energy_usage accepts ZIP code and date range to return electricity consumption for that specific area and period. Use query_by_date_range for any dataset with custom date filtering.

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