API Documentation

// Node.js example for data analysis and visualization
const axios = require('axios');
const { OpenAI } = require('openai');
const fs = require('fs');
const { ChartJSNodeCanvas } = require('chartjs-node-canvas');

class AppizerAnalytics {
  constructor(mcpApiKey, openaiApiKey) {
    this.mcpApiKey = mcpApiKey;
    this.mcpBaseUrl = 'https://api.appizer.com/mcp';
    this.openai = new OpenAI({ apiKey: openaiApiKey });
  }

  async getEventData(appId, eventName = null, days = 30, limit = 1000) {
    // Fetch event data for analysis
    const params = { app_id: appId, limit };
    if (eventName) params.event_name = eventName;
    
    try {
      const response = await axios.get(`${this.mcpBaseUrl}/events`, {
        headers: { 'X-MCP-API-Key': this.mcpApiKey },
        params
      });
      return response.data.events;
    } catch (error) {
      console.error('Error fetching event data:', error);
      return [];
    }
  }

  async analyzeEvents(appId, eventName) {
    // Get event data
    const events = await this.getEventData(appId, eventName);
    
    // Process data for analysis
    const eventsByDate = {};
    events.forEach(event => {
      const date = event.created_at.split('T')[0]; // Extract YYYY-MM-DD
      eventsByDate[date] = (eventsByDate[date] || 0) + 1;
    });
    
    // Convert to arrays for charting
    const dates = Object.keys(eventsByDate).sort();
    const counts = dates.map(date => eventsByDate[date]);
    
    // Create visualization using Chart.js
    const width = 800;
    const height = 500;
    const chartCallback = (ChartJS) => {
      // Optional: Global chart configuration
    };
    
    const chartJSNodeCanvas = new ChartJSNodeCanvas({ width, height, chartCallback });
    const configuration = {
      type: 'line',
      data: {
        labels: dates,
        datasets: [{
          label: `${eventName} Events Over Time`,
          data: counts,
          borderColor: 'rgb(75, 192, 192)',
          tension: 0.1
        }]
      },
      options: {
        scales: {
          y: { beginAtZero: true },
          x: { ticks: { maxRotation: 45 } }
        }
      }
    };
    
    // Generate chart image
    const image = await chartJSNodeCanvas.renderToBuffer(configuration);
    const vizPath = `${eventName}_trend.png`;
    fs.writeFileSync(vizPath, image);
    
    // Generate AI insights
    const dataForPrompt = dates.map((date, i) => `${date}: ${counts[i]}`).join('\n');
    const prompt = `
      Analyze this event data for ${eventName} events:
      ${dataForPrompt}
      
      Provide 3-5 key insights about user behavior patterns, anomalies,
      and recommendations based on this data.
    `;
    
    const completion = await this.openai.chat.completions.create({
      model: "gpt-4",
      messages: [
        { role: "system", content: "You are a data analyst providing insights on app usage patterns." },
        { role: "user", content: prompt }
      ]
    });
    
    return {
      visualization_path: vizPath,
      insights: completion.choices[0].message.content,
      raw_data: { dates, counts }
    };
  }
}

// Usage
const analytics = new AppizerAnalytics(
  'YOUR_MCP_API_KEY',
  'YOUR_OPENAI_API_KEY'
);

// Example analysis
async function runAnalysis() {
  const results = await analytics.analyzeEvents('app_123', 'purchase');
  console.log(results.insights);
}

runAnalysis();