@pipeworx/md-dmv
Connect: https://gateway.pipeworx.io/md-dmv/mcp · Install: one-click buttons
Tools: 2
Maryland DMV MCP — monthly registered-vehicle counts and electric/plug-in hybrid adoption by county and ZIP code, from the Maryland Motor Vehicle Administration (MVA).
Tools
md_dmv_vehicle_registrations(county?, month?, limit?)— registered vehicles by county for one month, with a genuine statewide total and each county’s share of it. Answers “how many vehicles are registered in Montgomery County Maryland”, “which Maryland county has the most registered vehicles”, “how many cars are registered in Maryland”.md_dmv_ev_adoption(county?, zip?, month?, group_by?, limit?)— battery-electric and plug-in hybrid registrations by county or by ZIP code for one month, with a Maryland total for context. Answers “how many EVs are registered in Montgomery County Maryland”, “EV registrations in ZIP 20852”, “which Maryland ZIP codes have the most EVs”.
Auth
Keyless.
Data sources
- https://opendata.maryland.gov/resource/db8v-9ewn.json — MDOT MVA registered vehicles by
county, monthly. Fields:
year_month(“2026/06”),county,vehicle_count. 25 rows per month (23 counties, Baltimore City, and aNULLbucket for registrations the MVA could not assign). - https://opendata.maryland.gov/resource/qtcv-n3tc.json — MDOT MVA electric and plug-in
hybrid registrations by county, monthly. Fields:
year_month,fuel_category(“Electric” | “Plug-In Hybrid”),county,count. ~464 rows per month. - https://opendata.maryland.gov/resource/tugr-unu9.json — same, by ZIP code. Fields:
year_month,fuel_category,zip_code,count. ~2,065 rows per month.
All three run monthly from 2020/07 to 2026/06 (latest as of 2026-07-29).
Gotcha: the Maryland WAF rejects query shapes, not queries
opendata.maryland.gov sits behind a Cloudflare WAF that answers certain SoQL query
shapes with a “Just a moment…” interstitial — HTTP 403 with an HTML body — instead of
data. It is reproducible, and it is specific to this one domain: data.ny.gov,
data.wa.gov and data.ct.gov all accept the identical clauses without complaint. It was
first hit from a deployed Cloudflare Worker, and has since been reproduced from a laptop
too, so it is a property of the request, not of the caller’s IP.
Confirmed to trip it:
| Shape | Example |
|---|---|
any like '%x%' wildcard clause | $where=upper(county) like '%MONTGOMERY%' |
a $where with two conditions joined by AND | $where=year_month='2026/06' AND county='MONTGOMERY' |
a $select with two aggregate expressions | $select=min(year_month) as mn, max(year_month) as mx |
Confirmed to work:
| Shape | Example |
|---|---|
a single year_month equality condition | $where=year_month='2026/06' |
a $select with one aggregate | $select=max(year_month) as mx |
So this pack sends exactly one condition, pulls the whole month (at most ~2,100 rows), and does all county/ZIP narrowing, aggregation and sorting in code. That is cheap, and it is the difference between the pack returning data and returning an HTML challenge page. Do not “optimise” the filtering back onto the server.
A side benefit: because the complete month is always in hand, statewide_total_vehicles
and maryland_plug_in_vehicles are real totals rather than sums of whatever survived
limit. The row-level sum is reported separately as sum_of_returned_rows.
Gotcha: the same county is spelled two different ways
The registration file and the EV files disagree on punctuation for the same places:
| Place | db8v-9ewn (registrations) | qtcv-n3tc / tugr-unu9 (EV) |
|---|---|---|
| Prince George’s County | PRINCE GEORGE'S | PRINCE GEORGES |
| St. Mary’s County | ST. MARY'S | ST MARYS |
| Queen Anne’s County | QUEEN ANNE'S | QUEEN ANNES |
Both tools fold punctuation away before matching, so a caller can pass either spelling.
Gotcha: the EV files carry out-of-state counties
Maryland records the registrant’s county (or ZIP) of residence, so qtcv-n3tc carries
~300 non-Maryland counties with small counts — ADAMS, ALAMEDA, ALBEMARLE and so on — mixed
in with the 24 Maryland jurisdictions. Every county row is flagged in_maryland, and
maryland_plug_in_vehicles counts only the Maryland ones.
The nastiest instance: Virginia’s PRINCE GEORGE sits right next to Maryland’s
PRINCE GEORGES, and Virginia’s is the exact match for the phrase “Prince George”. The
county resolver therefore returns both rows (flagged) rather than silently picking the
one-vehicle Virginia county over the 17,899-vehicle Maryland one.
Verified figures (2026/06, checked 2026-07-29)
| Query | Result |
|---|---|
md_dmv_vehicle_registrations{county:"Montgomery"} | 804,525 vehicles |
md_dmv_vehicle_registrations{} | 5,190,640 statewide |
md_dmv_ev_adoption{county:"Montgomery"} | 36,477 Electric + 12,319 Plug-In Hybrid |
md_dmv_ev_adoption{zip:"20852"} | 1,660 Electric + 566 Plug-In Hybrid |
md_dmv_ev_adoption{} | 153,463 Maryland plug-in vehicles |
Tools
- md_dmv_vehicle_registrations — Count vehicles registered in Maryland by county for a given month, from Maryland Motor Vehicle Administration (MVA) data published monthly since 2020. Returns each county’s registered-vehicle count pl
- md_dmv_ev_adoption — Measure electric-vehicle adoption in Maryland from Maryland MVA registration counts: how many battery-electric and plug-in hybrid vehicles are registered in a county or a ZIP code each month, split by
Tools
-
md_dmv_ev_adoption— Measure electric-vehicle adoption in Maryland from Maryland MVA registration counts: how many battery-electric and plug-in hybrid vehicles are registered in a county or a ZIP code each month, split by -
md_dmv_vehicle_registrations— Count vehicles registered in Maryland by county for a given month, from Maryland Motor Vehicle Administration (MVA) data published monthly since 2020. Returns each county's registered-vehicle count pl