# carvector-mcp

> Use this tool when you need to access accurate and reliable vehicle data, such as specifications, images, and recall information, to inform AI-driven decisions. CarVector-MCP solves problems of data hallucination by providing real vehicle data through its four tools: search_vehicles, get_vehicle, get_recalls, and lookup_dtc. It takes in authenticated client requests and returns relevant vehicle data, making it ideal for use cases requiring verified automotive information.

Canonical page: https://skillsregistry.net/skills/carvectorio-carvector-mcp  
JSON: https://api.skillsregistry.net/v1/skills/carvectorio-carvector-mcp

## Description

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.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/y0y8k9elnk)
- **Repository:** <https://github.com/carvectorio/carvector-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "carvectorio-carvector-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/carvectorio-carvector-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/carvectorio-carvector-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt