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carvector-mcp
Advanced tools
MCP server that gives your AI agent real vehicle data — specs, representative images, federal recalls, owner complaints, service bulletins, defect investigations, and OBD-II DTC reference — from the CarVector API.
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
· MIT · Free tier, no card → carvector.io
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" } } } }
| 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.
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.
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:
Calls count against your plan's rate limit and show up in your dashboard, exactly like a REST request.
This client is ~150 lines of readable JavaScript — please read them. It:
api.carvector.io (grep index.js, it's the only URL),Bearer header to that host, nowhere else,@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.
MIT. The client is open source; the data is served by CarVector.
FAQs
MCP server that gives your AI agent real vehicle data — specs, representative images, federal recalls, owner complaints, service bulletins, defect investigations, and OBD-II DTC reference — from the CarVector API.
The npm package carvector-mcp receives a total of 40 weekly downloads. As such, carvector-mcp popularity was classified as not popular.
We found that carvector-mcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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