AI-совместимый API автомобильных характеристик

import requests

API_KEY = 'YOUR_API_KEY'

# Natural language search - find vehicles by description
headers = {
    'Authorization': f'Bearer {API_KEY}',
    'Referer': 'https://yourwebsite.com'
}

response = requests.get(
    'https://v3.api.car2db.com/search/vehicles',
    headers=headers,
    params={'q': 'Toyota Camry 2.5 automatic'}
)

if response.status_code == 200:
    results = response.json()
    
    # Results grouped by models with relevance score
    for model in results.get('results', []):
        print(f"{model['model']['name']} ({model['matchingTrimsCount']} trims)")
        
        for trim in model.get('matchingTrims', []):
            print(f"  {trim['name']} ({trim['yearBegin']}-{trim['yearEnd']})")
            print(f"  Relevance: {trim['relevanceScore']}")
            
            # Key specs included in search results:
            specs = trim.get('keySpecifications', {})
            print(f"  Engine: {specs.get('engineVolume')}L {specs.get('power')}hp")
            print(f"  Transmission: {specs.get('transmission')}")
else:
    print(f"Error: {response.status_code}")

<?php
$apiKey = 'YOUR_API_KEY';

// Get trim with full context: breadcrumbs + key specs
// Replace 263119 with a real trim ID
$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://v3.api.car2db.com/trims/263119/full');
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer {$apiKey}",
    "Referer: https://yourwebsite.com"
]);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);

$response = curl_exec($ch);
$data = json_decode($response, true);
$trim = $data['trim'] ?? $data; // Handle both formats

if (isset($trim['breadcrumbs'])) {
    // Breadcrumbs provide full navigation context:
    $breadcrumbs = $trim['breadcrumbs'];
    echo "{$breadcrumbs['make']['name']} ";        // → "Toyota"
    echo "{$breadcrumbs['model']['name']} ";       // → "Camry"
    echo "{$breadcrumbs['generation']['name']} ";  // → "XV70"
    echo "{$trim['name']}\n";                      // → "2.5 AT"
    
    // Key specifications optimized for AI/LLM:
    $specs = $trim['keySpecifications'] ?? [];
    echo "Engine: {$specs['engineVolume']} cm\n";    // → "2496 cm"
    echo "Power: {$specs['power']}hp\n";           // → "200hp"
    echo "Drive: {$specs['drive']}\n";             // → "Front"
}

API_KEY="YOUR_API_KEY"

# Get equipment with ALL options grouped by category
curl -X GET "https://v3.api.car2db.com/equipments/54321/full" \
     -H "Authorization: Bearer $API_KEY" \
     -H "Referer: https://yourwebsite.com"

# Response includes complete equipment data in one request:
{
  "equipment": {
    "id": 54321,
    "name": "Prestige",
    "breadcrumbs": {
      "make": { "id": 10, "name": "Toyota" },
      "model": { "id": 120, "name": "Camry" }
    }
  },
  "options": {
    "Safety": [
      { "name": "Airbags", "value": "8" },
      { "name": "ABS", "value": "Standard" }
    ],
    "Comfort": [
      { "name": "Climate Control", "value": "Dual-zone" },
      { "name": "Heated Seats", "value": "Front & Rear" }
    ],
    "Multimedia": [
      { "name": "Display", "value": "10.1 inch touchscreen" }
    ]
  }
}

# Zero-code AI Integration
# Connect Claude Desktop, Cursor, VS Code to Car2DB API

## Claude Desktop Configuration
# File: claude_desktop_config.json
{
  "mcpServers": {
    "car2db": {
      "command": "npx",
      "args": ["-y", "@car2db/mcp-server"],
      "env": {
        "CAR2DB_API_KEY": "your_api_key_here",
        "CAR2DB_LANGUAGE": "en-US"
      }
    }
  }
}

## GitHub Copilot / VS Code Configuration
# File: .vscode/mcp.json
{
  "mcpServers": {
    "car2db": {
      "command": "npx",
      "args": ["-y", "@car2db/mcp-server"],
      "env": {
        "CAR2DB_API_KEY": "your_api_key_here",
        "CAR2DB_LANGUAGE": "en-US"
      }
    }
  }
}

# Now ask AI: "Find specifications for Toyota Camry 2.5"
# AI will automatically use Car2DB API via MCP Server!