pa-dmv

pa-dmv

Query Pennsylvania DMV data for EV adoption and vehicle registrations by county and ZIP code.

Category
Visit Server

README

@pipeworx/pa-dmv

Pennsylvania DMV MCP — registered vehicles and electric-vehicle adoption by county and by ZIP code, from PennDOT Driver & Vehicle Services.

Tools

  • pa_dmv_ev_adoption(county?, year?, quarter?, limit?) — battery-electric, plug-in hybrid, fuel-cell and conventional hybrid registrations for each of Pennsylvania's 67 counties in one quarter, with plug-in share and a genuine statewide total. Answers "how many EVs are registered in Pennsylvania", "EV share in Allegheny County", "which Pennsylvania county has the most electric vehicles".
  • pa_dmv_vehicle_registrations(county?, year?, quarter?, limit?) — the whole registered fleet of every fuel type by county, with a statewide total and each county's share. Rides on the same layer, which carries TOTAL_REG alongside the EV columns.
  • pa_dmv_ev_adoption_by_zip(zip?, year?, quarter?, limit?) — the same drivetrain breakdown for ~1,830 Pennsylvania ZIP codes. Answers "how many EVs are registered in ZIP 19103", "which Pennsylvania ZIP code has the most electric vehicles".

Auth

Keyless.

Data sources

Both layers have maxRecordCount 2000, so a full year fits in a single request and no paging is needed. Latest published quarter as of 2026-07-29 is 2026 Q2.

Gotcha: quarters are COLUMNS, not rows

Each feature is one county (or ZIP) for one REGISTRATION_YEAR, carrying all four quarters side by side as separate column groups. Quarters PennDOT has yet to file are present as null columns. There is no row to filter on and no date field to sort by, so "the latest data" means walking Q4 → Q1 looking for a quarter that actually carries values.

pickQuarter() does that walk once for the whole result set, not per row. Picking a quarter per row looks harmless on a single-county lookup and is a correctness bug on a ranking: you end up comparing one county's Q2 against another's Q1 and summing the mix into a "statewide total". A quarter is accepted only if at least half as many rows carry it as carry the best-covered quarter, so one early-reporting straggler cannot drag the whole answer forward.

Gotcha: hybrids sit outside TOTAL_EV

PennDOT's TOTAL_EV = BEV + PHEV + FUEL_CELL. Conventional hybrids (HEV) are reported separately and are deliberately excluded — a Prius appears in hybrid_gasoline and never in plug_in_vehicles. Verified across all 67 counties × both 2026 quarters: zero mismatches between TOTAL_EV and BEV + PHEV + FUEL_CELL.

Gotcha: the ZIP layer's 2026 Q1 columns are wrong upstream

In the ZIP layer only, and in the 2026 Q1 column group only, PennDOT's own derived columns are broken two ways:

  • TOTAL_EV_Q1 folds conventional hybrids in. ZIP 19103 publishes TOTAL_EV_Q1 1291 against BEV_Q1 314 + PHEV_Q1 136 + HEV_Q1 841 = 1291.
  • PCT_EV_Q1 is written as a fraction of that inflated number rather than a percent. ZIP 19103 publishes 0.14 where the plug-in share is 4.85%.

Every other year, quarter and layer is internally consistent. So this pack computes plug_in_vehicles and ev_share_pct from the component columns everywhere rather than reading TOTAL_EV / PCT_EV — which reproduces PennDOT's published values exactly wherever those are sound (Montgomery County 2026 Q1 → 22,606 and 2.87, matching), and quietly repairs them where they are not.

Gotcha: the ZIP file undercounts the state by ~0.5%

Summing every ZIP code gives 12,039,085 registered vehicles for 2026 Q2 against the county layer's 12,098,320 — a few registrations carry no usable ZIP code. pa_dmv_ev_adoption (county layer) is the authoritative statewide number; the ZIP tool labels its own sums zip_file_total_vehicles rather than claiming a state total.

Verified figures (checked 2026-07-29)

Query Result
pa_dmv_ev_adoption{county:"Montgomery", year:"2026", quarter:"Q1"} BEV 16,243 · PHEV 6,363 · plug-in 22,606 · HEV 45,763 · total 788,762 · share 2.87%
pa_dmv_ev_adoption{county:"Allegheny", year:"2026"} (Q2) plug-in 19,350 · total 965,589
pa_dmv_ev_adoption{} (2026 Q2) statewide 171,670 plug-in of 12,098,320 registered, 1.42%
pa_dmv_ev_adoption_by_zip{zip:"19103", year:"2026"} (Q2) BEV 337 · PHEV 131 · plug-in 468 · total 9,322 · share 5.02%

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "pa-dmv": {
      "url": "https://gateway.pipeworx.io/pa-dmv/mcp"
    }
  }
}

Or connect to the full Pipeworx gateway for access to all 1392+ data sources:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English:

ask_pipeworx({ question: "your question about Pennsylvania DMV (PennDOT) data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured