PG&E Data Portals MCP Server
Search and query PG&E energy datasets: usage, EV adoption, solar, grid data.
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What is the PG&E Data Portals MCP Server?
The PG&E Data Portals MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to PG&E Data Portals via 10 tools. Search and query PG&E energy datasets: usage, EV adoption, solar, grid data. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (10)
Tools for your AI Agents to operate PG&E Data Portals
Ask your AI agent "List all available PG&E datasets." and get the answer without opening a single dashboard. With 10 tools connected to real PG&E Data Portals data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
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PG&E Data Portals MCP Server capabilities
10 toolsUse this to understand what columns and data types are available before querying. The datasetId is obtained from search_datasets or list_all_datasets. Get the schema/metadata for a specific PG&E dataset
Each dataset includes name, description, ID, and metadata. Use this as a starting point to explore what data is available from PG&E — includes energy usage, EV adoption, solar generation, energy efficiency programs, and grid infrastructure datasets. List all available datasets in the PG&E Data Portals catalog
Specify the dataset ID and start/end dates to retrieve records within that time period. Use this for time-series analysis across any dataset type. Dataset ID from search_datasets. Dates in YYYY-MM-DD format. This is useful for year-over-year comparisons and trend analysis. Query any PG&E dataset filtered by a specific date range
Optional filters can be passed as key-value pairs to narrow results (e.g., zip_code, year, region). Use this to retrieve actual data records from any dataset in the PG&E Data Portals. Dataset IDs are obtained from search_datasets or list_all_datasets. Query a specific PG&E dataset with optional filters
), and investment amounts. Use this to analyze program effectiveness and ROI of energy efficiency initiatives. Optional programType filters by program category. Year is YYYY format. Query PG&E energy efficiency program data
Returns electricity usage aggregated by customer segment (residential, commercial, industrial, agricultural). Use this to analyze energy consumption patterns in specific geographic areas over time. ZIP code format: 5-digit (e.g., "94102"). Dates in YYYY-MM-DD format. Query PG&E energy consumption data by ZIP code and date range
Use this to analyze EV adoption trends, identify high-adoption areas, and correlate with charging infrastructure. ZIP code is 5-digit format. Year is YYYY format (e.g., "2024"). Query electric vehicle adoption data by ZIP code and year
Use this to understand grid capacity, identify areas needing upgrades, or analyze reliability metrics. Region filters by geographic area. dataType can filter by specific infrastructure type. Query PG&E grid infrastructure and distribution data
Use this to analyze solar adoption and production trends. Region can be a county name or service area identifier. Year is YYYY format. Query solar energy generation data by region and year
Use this to discover available datasets before querying specific data. Returns dataset names, descriptions, IDs, and metadata. Optional query parameter filters results by keyword. Search the PG&E Data Portals catalog for energy datasets
What the PG&E Data Portals MCP Server unlocks
Connect PG&E Data Portals to any AI agent and programmatically search, discover, and query PG&E's public energy datasets through natural conversation.
What you can do
- Dataset Search — Search the complete PG&E Data Portals catalog for energy-related datasets
- Energy Usage — Query electricity and gas consumption data by ZIP code and date range
- EV Adoption — Access electric vehicle registration and adoption trends by geographic area
- Solar Generation — Retrieve solar energy production and net energy metering (NEM) statistics
- Energy Efficiency — Analyze program participation, energy savings achieved, and cost-effectiveness
- Grid Infrastructure — Access distribution circuit, substation, and grid capacity data
- Date Range Queries — Filter any dataset by specific time periods for trend analysis
- Dataset Metadata — Get schema information and field descriptions for all datasets
How it works
1. Subscribe to this server 2. (Optional) Enter your PG&E Data Portals API Key for higher rate limits 3. Start exploring PG&E energy data from Claude, Cursor, or any MCP-compatible clientWho is this for?
- Energy Analysts — analyze consumption trends, EV adoption patterns, and solar generation data
- Urban Planners — access grid infrastructure and regional energy consumption data
- Researchers — query time-series energy data for academic and policy studies
- Clean Tech Companies — identify high-potential markets for EV charging, solar, and efficiency products
Frequently asked questions about the PG&E Data Portals MCP Server
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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