Carvector
БесплатноНе проверенCarVector is a Model Context Protocol server that gives AI agents real vehicle data — specifications and representative images, federal recall campaigns, and OB
Описание
CarVector is a Model Context Protocol server that gives AI agents real vehicle data — specifications and representative images, federal recall campaigns, and OBD-II DTC reference — instead of hallucinating them. Open-source client (npx -y carvector-mcp), authenticated with your own key; free tier, no credit card. Four tools: search_vehicles, get_vehicle, get_recalls, lookup_dtc.
README
Give your AI agent real vehicle data. An MCP server that lets Claude, Cursor, ChatGPT, or any MCP-capable client query the CarVector API natively — vehicle specs, representative images, federal recalls, owner complaints, service bulletins, defect investigations, and OBD-II diagnostic trouble codes.
Models hallucinate car data. They invent horsepower numbers, miss recalls filed last week, and guess at what a trouble code means. carvector-mcp gives your agent structured, sourced answers it can cite instead of a confident guess.
npx -y carvector-mcp --key cv_your_key
npm · MIT · Free tier, no card → carvector.io
Quickstart
1. Get a free API key at carvector.io — 500 requests a month, no credit card.
2. Add it to your MCP client. Most clients use an mcpServers block:
{
"mcpServers": {
"carvector": {
"command": "npx",
"args": ["-y", "carvector-mcp"],
"env": { "CARVECTOR_API_KEY": "cv_your_key" }
}
}
}
That's it. Restart your client and ask it about a vehicle.
Prefer a remote server? If your client supports HTTP MCP, skip the install and point it straight at the hosted endpoint:
{ "mcpServers": { "carvector": { "url": "https://api.carvector.io/v1/mcp", "headers": { "Authorization": "Bearer cv_your_key" } } } }
Tools
| Tool | What it returns |
|---|---|
search_vehicles |
Matching vehicles by year / make / model, with ids + specs |
get_vehicle |
Full specs for one vehicle — engine, drivetrain, body, image, recall count |
get_recalls |
Federal recall campaigns for a vehicle — component, summary, consequence, remedy |
get_complaints |
Owner-complaint signal for a vehicle — aggregate by component + the most recent complaints (Pro plan) |
get_tsbs |
Manufacturer service-bulletin index for a vehicle — the fix the dealer already knows about (Business plan) |
get_investigations |
Federal defect investigations for a vehicle — a leading indicator of recalls (Business plan) |
lookup_dtc |
An OBD-II code's title, category, severity, and safety/emissions flags |
The agent chains them naturally: search_vehicles to resolve an id, then get_vehicle, get_recalls, get_complaints, get_tsbs, or get_investigations.
Example
You: "Is a P0300 code serious?"
→ carvector.lookup_dtc({ code: "P0300" })
{
"code": "P0300",
"title": "Random/Multiple Cylinder Misfire Detected",
"category": "Powertrain",
"severity": "High",
"safety_risk": true,
"emissions_related": true
}
Your agent answers: "Yes — P0300 is a high-severity, safety-related misfire code. Don't keep driving on it." Sourced, not guessed.
Three things to build with it
- A service-advisor copilot that pulls a customer's exact trim, open recalls, the manufacturer's documented fix (TSBs), the complaint pattern behind a symptom, and a decoded check-engine code — in one turn, no tab-switching.
- A consumer car chatbot that answers "what engine does my truck have" and "is it under recall" with real data instead of a hallucination.
- A coding/automotive agent that needs structured vehicle knowledge as a tool, not a wall of scraped text to parse.
About the data
carvector-mcp is an open-source, thin client. It bundles no data — every call forwards to the CarVector API, authenticated with your key. What you get back:
- Vehicles — a broad catalog (1925–2029), broken out by trim and engine variant, with representative illustrations (not photos).
- Recalls — federal recall campaigns mapped to year / make / model.
- Complaints — owner-filed complaints aggregated by component (with crash / fire / injury counts) plus the most recent filings, mapped to a vehicle. (Pro plan.)
- Service bulletins (TSBs) — the manufacturer's technical service-bulletin index — metadata, not the documents. (Business plan.)
- Investigations — federal defect investigations, a leading indicator that often precedes a recall. (Business plan.)
- DTC reference — OBD-II codes classified by category, severity, and safety/emissions flags. Reference only — repair-cost economics is on the roadmap, not in responses today.
Calls count against your plan's rate limit and show up in your dashboard, exactly like a REST request.
Open source & your key
This client is ~150 lines of readable JavaScript — please read them. It:
- talks to one host only —
api.carvector.io(grepindex.js, it's the only URL), - sends your key only as a
Bearerheader to that host, nowhere else, - has zero telemetry, analytics, or phone-home, and writes nothing to disk,
- depends on exactly one package: the official @modelcontextprotocol/sdk.
Your key stays on your machine. Set it via the CARVECTOR_API_KEY env var (preferred); --key works too but, like any CLI argument, is visible in process listings.
License
MIT. The client is open source; the data is served by CarVector.
Установка Carvector
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/carvectorio/carvector-mcpFAQ
Carvector MCP бесплатный?
Да, Carvector MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Carvector?
Нет, Carvector работает без API-ключей и переменных окружения.
Carvector — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Carvector в Claude Desktop, Claude Code или Cursor?
Открой Carvector на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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