EV Charging Stations Scraper – OpenStreetMap Charger Data

Extract electric-vehicle charging stations from OpenStreetMap by area, radius, or name — no API key, no rate-limited charging-network API, no anti-bot battles. Open, legal (ODbL) data you can redistribute.

Give it an area like "Amsterdam, Netherlands" and get back tidy rows for every EV charger: name, operator, network, number of charging points, socket types, maximum power (kW), fee, access, full address, coordinates, and the raw OpenStreetMap tags. You can also search around a point (every charger within X km of an address) or filter by name/network (e.g. every "Tesla" or "Ionity" station).

Why use this scraper?

• EV-specific fields. Not just a generic POI dump — socket types, max power in kW, per-socket counts, capacity, fee and access are parsed out of the OpenStreetMap tags for you.
• Legal & open. OpenStreetMap data is licensed under the ODbL — redistributable with attribution. No Terms-of-Service violation, no login.
• No API key. No charging-network developer account, no per-call quota.
• Search by area, radius, or name/network. A whole city/country, everything within X metres of a point, or every station of one operator.
• No duplicates. When OpenStreetMap maps one station twice (a node and an area), you get a single, richer row.
• Honest data. Every value comes straight from OpenStreetMap; anything not mapped is left empty (null) — never guessed or padded. max_power_kw is read only from explicit power tags.
• Global coverage & reliable. Anywhere OSM has data; retries across multiple Overpass mirrors.

Great for

• EV apps, route planners, and charger-finder maps
• Charging-network market research and coverage analysis
• Site selection for new charging infrastructure
• Fleet & mobility datasets, dashboards, and AI/RAG pipelines

Input

Field	Type	Description
area	string	Place to search within, e.g. "London, United Kingdom". Geocoded to a bounding box.
aroundLocation	string	(optional) Address/place to search around within a radius, e.g. "Schiphol Airport". Pair with radiusMeters.
radiusMeters	integer	(optional) Radius in metres for around-a-location search (default 5000).
centerPoint	object	(advanced) Explicit center { "lat":.., "lon":.. } to search around.
boundingBox	object	(advanced) Explicit { "south":.., "west":.., "north":.., "east":.. }. Overrides area.
searchTerm	string	(optional) Only return stations whose name contains this text (case-insensitive), e.g. "Tesla".
maxResults	integer	Maximum number of stations to return (default 1000).

Example input

{
  "area": "Amsterdam, Netherlands",
  "maxResults": 500
}

Every Tesla station within 10 km of a point:

{
  "aroundLocation": "Utrecht Centraal",
  "radiusMeters": 10000,
  "searchTerm": "Tesla"
}

Output

One row per charging station:

Field	Description
name	Station name
operator, brand, network	Who runs / brands / networks the station
branch	Branch / location name of a chain outlet (OSM branch), e.g. Times Square; null when not a tagged branch
brand_wikidata	Wikidata id of the brand/network (e.g. Q478214) — stable entity id for analysis, when tagged
brand_logo	Official brand logo image URL, from the brand's Wikidata entity (P154) when it has one; null otherwise. Optional enrichment — never guessed
capacity	Number of charging points
max_power_kw	Highest charging power in kW found across the station's power tags
socket_types	Array of socket types present, e.g. ["type2","ccs","chademo"]
capacity_by_socket	Map of socket type → count, when OSM tags a per-socket count
fee, access	Whether a fee applies; access (public / customers / …)
latitude, longitude	Coordinates
street, housenumber, city, postcode, country	Address
state	State / province (addr:state / addr:province); common in US/CA/AU, null where not tagged
phone, website, opening_hours	Contact + hours
osm_id, osm_type, all_tags, source_url	OpenStreetMap identifiers, raw tags, and link
full_address	All present address parts in one string (e.g. Main St 1, 10115 Berlin)
map_url	Google Maps link to the coordinates

Example output

{
  "name": "London - Canary Wharf Supercharger",
  "operator": "Tesla",
  "brand": "Tesla Supercharger",
  "network": "Tesla",
  "capacity": 12,
  "max_power_kw": 250,
  "socket_types": ["tesla_supercharger", "tesla_supercharger_ccs", "type2_combo"],
  "capacity_by_socket": { "tesla_supercharger": 12 },
  "fee": "yes",
  "access": "customers",
  "city": "London",
  "postcode": "E14 5EW",
  "country": "GB",
  "latitude": 51.5049,
  "longitude": -0.0195,
  "osm_type": "node",
  "source_url": "https://www.openstreetmap.org/node/..."
}

Any field is null (or an empty array) when the station hasn't tagged it in OpenStreetMap — values are never guessed.

FAQ

Do I need an API key or account? No — give it an area (plus optional radius/name filters) and run. No data-provider key, no quota, no setup.

Is the data legal to use and redistribute? Yes. It comes from OpenStreetMap under the Open Database License (ODbL): public data you can redistribute with attribution (© OpenStreetMap contributors). No logins, no Terms-of-Service violations.

How is this different from a Google Maps or PlugShare scraper? It uses open OpenStreetMap data instead of scraping a site behind anti-bot defenses and Terms of Service — so it's legal, needs no API key, and returns an honest null for anything OSM hasn't mapped instead of guessing. You also get charger-specific fields like socket types and power (kW).

How much does it cost? Pay-per-result: $3 per 1,000 results — you only pay for the rows you actually get.

Which countries does it cover? Worldwide — anywhere OpenStreetMap has data.

How fresh is the data? It's pulled live from OpenStreetMap at run time, so it reflects the current map.

Data source & license

Data comes from OpenStreetMap via the public Nominatim (geocoding) and Overpass (querying) APIs. OpenStreetMap data is © OpenStreetMap contributors, licensed under the Open Database License (ODbL). If you publish or redistribute results, attribute "© OpenStreetMap contributors".

Notes

• Coverage and tag richness vary by region — OSM is community-mapped, so dense urban areas are richer.
• Charging stations are sparser than general POIs, so the radius default is wider (5 km).

More OpenStreetMap data actors

Part of dataquarry's family of clean, ODbL OpenStreetMap extractors — same flexible area / radius / bounding-box / name search, same honest-null data (a field that isn't mapped is left empty, never guessed):

• OpenStreetMap Places Scraper — POI & local business, 115+ categories
• EV Charging Stations Scraper — socket types, power (kW), networks
• Hotels & Lodging Scraper — stars, rooms, brands
• Healthcare Facilities Scraper — pharmacies, doctors, dentists, clinics
• Tourist Attractions & Museums Scraper — Wikidata & Wikipedia links
• Fuel Station Scraper — fuel types, brands, payment methods
• Supermarket & Grocery Scraper — brands, organic, payment methods