openvehicle-data

Open, verified data on passenger cars: brands, models, versions and technical specifications, for the cars registered in Italy from 2019 to 2025 (EU category M1), with Europe and the world to follow.

It is published three ways, all read-only and free:

• a dataset (SQLite, CSV and JSON) on the Releases page;

• a REST API with interactive documentation;

• an MCP server, so AI agents can look vehicles up themselves.

Every technical value says where it comes from, and where two sources agree it says so. There is no personal data: no owners, no plates, no VIN lookups.

Status: early development. Datasets are pre-releases (data-v* tags) and the schema can still change. See Limits before relying on it.

Contents

Try it · The data · REST API · MCP server · Run it yourself · Limits · Contributing · Documentation · Licenses

Related MCP server: ECRVSP Processos: Imprimir CRLV-e

Try it

With a server running (see Run it yourself), on its default local address:

U=http://localhost:8000/api/v1

# find a model by name (typos get a "did_you_mean")
curl "$U/search?q=panda"

# the most registered Toyota variants seen in 2023
curl "$U/variants?brand_id=brand_toyota&year=2023&sort=registrations&limit=5"

# one variant, with its engine and the source of every field
curl "$U/variants/var_fiat-panda-312-pyd1b-s5g"

# match the number on an Italian registration document (carta di circolazione)
curl "$U/variants?type_approval=e3*2007/46*0064*05"

Interactive documentation is at /docs on the same host.

The data

Structure

Brand ─ Family ─ Model ─ Generation ─ Variant ─ Engine
FIAT    PANDA    PANDA    observed    312 PYD1B S5G   hybrid 999 cc 52 kW

Ids are stable and readable. Lists are sorted by id in the REST API and by registrations in the MCP server, and both accept min_registrations to skip rare or mistyped entries.

What a variant holds

Brands also carry a wikidata_id where a reliable match was reviewed.

Where each value comes from

Every technical field (mass, CO2, wheelbase, track width, engine size and power, type approval, Wikidata id) has its own record: source, licence, evidence link, last_verified date and a status. get_variant and GET /variants/{id} return them.

confirmed is a check against transcription and aggregation errors, not a second measurement: both sources derive from the manufacturer's type-approval data.

RDW rows are one per licence plate, so they are grouped on the RDW server: no plate is stored, published or logged.

Downloads

Each release has openvehicle-data.db (SQLite), one CSV per table (brands, families, models, generations, engines, variants, provenance, sources), dataset.json, manifest.json (SHA-256 of every file) and a changelog against the previous release.

REST API

Base path /api/v1. Everything is GET.

Lists take limit (default 50, at most 200) and offset, and answer with total, count, has_more and next_offset. sort is id or registrations. type_approval accepts the full number as printed on the registration document or only its base. An unknown id gives a 404 with a "Did you mean" suggestion; a malformed value gives a 422.

MCP server

Endpoint /mcp (Streamable HTTP, stateless, no authentication). Add your server to an MCP client, for example Claude Code:

claude mcp add --transport http openvehicle http://localhost:8000/mcp

Names and codes come from public datasets, so the server tells clients to treat them as data, never as instructions, and it replaces oversized or non-printable strings. Ask an agent, for instance: "Which diesel Peugeot 3008 variants were registered in 2022, and what is the source of their CO2 value?"

Run it yourself

Python 3.12 or newer.

python -m venv .venv
.venv/Scripts/pip install -e ".[dev]"      # Linux/macOS: .venv/bin/pip

# build the dataset: downloads 2019-2025 from the EEA and the RDW (about 4 minutes),
# validates, and exports to ./dist  (--skip-rdw skips the RDW cross-check)
python -m pipeline.build --years 2019-2025 --version 0.1.0 --out dist

# serve the REST API (docs at /docs) and the MCP server (at /mcp)
OVD_DB=dist/openvehicle-data.db uvicorn --factory service.app:create_app

--years also takes one year (2025) or a list (2021,2023); --prev <folder> compares with a previous export and writes the changelog. The build stops without writing anything if validation finds an error.

Docker: the image downloads a pinned data release and checks its SHA-256.

docker build -t openvehicle-data . && docker run -p 10000:10000 openvehicle-data

Tests, with the required 100% coverage:

coverage run -m pytest tests/ -q && coverage report

A monthly GitHub Actions job rebuilds the data and opens an issue if anything changed; it never publishes by itself. Deployment (Render, data releases, a custom domain) is described in DEPLOY.md.

Limits

• Cars only (category M1). No vans, trucks or motorcycles, no trims or equipment, no prices.

• Only vehicles registered in Italy, 2019-2025. Years are registration years.

• Names are as the EEA reports them, in upper case. Spellings that differ only by spaces, hyphens or case are merged; a few near-duplicates remain.

• Family rules cover 48 brands; the other brands keep one family per model.

• Wheelbase and track width exist only for 2019-2022 (the EEA stopped reporting them).

• RDW covers about half of the variants (cars sold in the Netherlands), so the rest stay single_source. CO2 is single-source everywhere: RDW's per-plate values vary too much between cars of one variant to serve as a check.

• Wikidata ids exist for 56 of 90 brands; models are not linked (Wikidata has duplicate and mixed items for them).

• The API has no authentication and no rate limiting of its own: put it behind a proxy that limits requests if you expose it publicly (see DEPLOY.md).

Contributing

Known mistakes in the sources are fixed through small reviewed files, each entry with a written reason, so a proposal is a pull request that edits one of them:

Work goes through issues and pull requests to dev; main only receives reviewed releases. Keep the 100% test coverage. Please do not put personal data in issues.

Documentation

• ADR.md: architecture decisions and the measurements behind them (in Italian)

• DEPLOY.md: data releases, Render, domain and rate limiting

• PRIVACY.md: what the public service processes

• NOTICE: sources and their licences

• Layout: core/ models and storage · pipeline/ import, validation and export · service/ API and MCP server

Licenses and attribution

• Code: Apache-2.0 (LICENSE).

• Data: CC BY 4.0 (LICENSE-DATA); sources and their licences in NOTICE.

If you use the data, cite: Data from openvehicle-data (https://github.com/mirkobechini/openvehicle-data), CC BY 4.0. See NOTICE for upstream sources. The same text is returned by dataset_info and /meta.

Disclaimer

The data is provided "as is", without warranty of any kind. Verify it before any safety-critical use. This project is not affiliated with any vehicle manufacturer; brand and model names are trademarks of their respective owners.