@builderz/maiker-analytics-sdk v0.1.3

Maiker Analytics SDK

The Maiker Analytics SDK provides TypeScript clients for accessing Maiker Analytics data through multiple interfaces:

• HTTP API Client: Access analytics via REST API endpoints (recommended for client-side applications)
• Direct Database Client: Direct PostgreSQL access for server-side applications
• Strategy Client: On-chain Solana strategy data access

Installation

npm install @builderz/maiker-analytics-sdk
# or
yarn add @builderz/maiker-analytics-sdk

HTTP API Client (Recommended)

The HTTP API client provides a clean interface to the Maiker Analytics API:

import { MaikerAnalyticsApiClient } from '@builderz/maiker-analytics-sdk';

// Initialize client
const client = new MaikerAnalyticsApiClient({
  baseUrl: 'https://api.maiker.fun', // Optional, defaults to production
  timeout: 30000, // Optional, defaults to 30 seconds
});

// Get all token pairs with statistics (includes volume, fees, TVL data)
const tokenMaps = await client.getPairTokenMaps();

// Get timeseries data (v2 endpoint optimized for charting)
const timeseries = await client.getLbPairTimeseries(
  ['lb_pair_1', 'lb_pair_2'],
  {
    start_timestamp: Math.floor(Date.now() / 1000) - 24 * 60 * 60, // Last 24 hours
  },
  '1h' // Hourly granularity
);

// Fee concentration analysis
const feeData = await client.getFeeConcentration('lb_pair_address');

// Position analytics
const positionPnL = await client.getPositionPnL('position_id');
const positionTimeseries = await client.getPositionTimeseries('position_id');
const userPositions = await client.getUserPositions('owner_address');

// Session analytics (all positions for owner/lb_pair)
const sessionPnL = await client.getSessionPnL('owner_address', 'lb_pair_address');
const sessionTimeseries = await client.getSessionTimeseries('owner_address', 'lb_pair_address');

Available Endpoints

Pairs API

• getPairTokenMaps(): Get all token pairs with LB pairs and statistics (volume, fees, TVL across multiple timeframes)
• getLbPairTimeseries(lbPairs, timeRange?, granularity?): Get timeseries data optimized for charting

Analysis API

• getFeeConcentration(lbPair, startTimestamp?): Get fee concentration analysis

Position Analytics API

• getPositionPnL(positionId, timeRange?): Get single position PnL analysis
• getPositionTimeseries(positionId, timeRange?): Get single position timeseries data
• getUserPositions(owner): Get positions for a specific owner
• getSessionPnL(owner, lbPair, timeRange?): Get session PnL for all positions of owner/lb_pair
• getSessionTimeseries(owner, lbPair, timeRange?): Get session timeseries for all positions

Direct Database Client

For server-side applications with direct database access:

import { AnalyticsClient } from '@builderz/maiker-analytics-sdk';

const client = new AnalyticsClient({
  connectionString: 'postgresql://user:pass@host:port/db',
  ssl: true,
});

// Use the various analytics modules
const positionAnalytics = await client.positions.getAnalytics('position_id');
const pairAnalytics = await client.pairs.getAnalytics('lb_pair');

Types

All TypeScript types are exported for use in your applications:

import {
  TokenPair,
  LBPair,
  TimeseriesDataPoint,
  PositionPnLResult,
  PositionTimeseriesResult,
  TokenMapsResponse,
  TimeRange,
  TimeGranularity,
} from '@builderz/maiker-analytics-sdk';

Environment Configuration

The HTTP API client automatically detects environment:

// For local development
process.env.NEXT_PUBLIC_LOCAL_API = 'true'; // Uses http://localhost:3000

// For production (default)
// Uses https://api.maiker.fun

Error Handling

All clients include comprehensive error handling:

try {
  const data = await client.getPairTokenMaps();
} catch (error) {
  console.error('API Error:', error.message);
  // Handle error appropriately
}

API Reference

Time Ranges

interface TimeRange {
  start_timestamp?: number; // Unix timestamp in seconds
  end_timestamp?: number;   // Unix timestamp in seconds
}

Time Granularities

• TimeGranularity: '15m' | '1h' | '4h' | '12h' | '24h'

Contributing

1. Fork the repository
2. Create your feature branch
3. Add tests for new functionality
4. Ensure all tests pass
5. Submit a pull request