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Multichain Wallet Analytics API

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$10.00 / 1,000 results

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Multichain Wallet Analytics API

Multichain Wallet Analytics API

Developed by

Merkle

Maintained by Community

The fastest & cheapest API to scrape wallet trading stats across multiple blockchains. Instantly access PnL, trade history, win/loss ratio & performance metrics for any crypto wallet. Perfect for analysts, traders, and bot builders

0.0 (0)

Pricing

$10.00 / 1,000 results

1

Monthly users

3

Last modified

a day ago

Multichain Wallet Analytics API (GMGN)

Multichain Wallet Analytics API (GMGN) is a lightning-fast, budget-friendly Apify actor that gathers and analyzes deep trading metrics from up to 3 crypto wallets across leading blockchains (Ethereum, BSC, Base, Solana and Blast). Perfect for analysts, traders, and bot developers, it delivers actionable PnL figures, win/loss ratios, and performance insights in seconds.

Why Choose Multichain Wallet Analytics API (GMGN)?

  • Fastest Analytics: Accelerated scraping engine provides wallet stats within seconds
  • Most Cost-Effective: Streamlined resource usage cuts down on API and proxy costs
  • Up to 3 Wallets: Caps queries at 3 wallets per run for reliable, consistent performance
  • Deep Insights: Comprehensive PnL ratios, trade counts, risk metrics, and more
  • Multi-Chain Coverage: Supports Ethereum, BSC, Base, Solana, and Blast
  • Flexible Timeframes: Retrieve data over 1-day, 7-day, 30-day, or all-time periods

Features

  • Scrape detailed statistics for up to 3 wallet addresses simultaneously
  • Fetch metrics for customizable periods: 1d, 7d, 30d, all
  • Export results to Apify dataset in JSON, CSV, or Excel format
  • Automatic wallet address validation and format conversion
  • Multi-chain support: eth, bsc, base, sol, blast

Use Cases

  • Portfolio Analysis: Measure ROI and monitor wallet performance over time
  • Risk Profiling: Identify high-risk trading patterns and exposure levels
  • Investor Research: Uncover strategies and behaviors of successful wallets
  • Market Studies: Compare asset performance and trading strategies across wallets
  • Data Science Projects: Generate rich datasets for machine learning and statistical analysis

Usage

  1. Run this actor in the Apify console.
  2. Provide inputs:
    • walletAddresses: Array of wallet addresses (max 3)
    • chain: One of eth, bsc, base, sol, blast
    • period: One of 1d, 7d, 30d, all

Example Input

1{
2    "walletAddresses": ["0xd8da6bf26964af9d7eed9e03e53415d37aa96045"],
3    "chain": "eth",
4    "period": "all"
5}

Output

The collected data is saved to the Apify dataset with the following fields:

FieldDescription
wallet_addressWallet address
chainBlockchain network
periodTimeframe of statistics
Trading Counts
buy, buy_1d, buy_7d, buy_30dNumber of buys overall and by period
sell, sell_1d, sell_7d, sell_30dNumber of sells overall and by period
Profit / Loss
pnl, pnl_1d, pnl_7d, pnl_30dProfit/Loss ratios overall and by period
all_pnlAll-time profit/loss ratio
realized_profit, realized_profit_1d, realized_profit_7d, realized_profit_30dRealized profits overall and by period
unrealized_profit, unrealized_pnlUnrealized profit and P/L ratio
total_profit, total_profit_pnlTotal profit and profit/L ratio
Balances & Value
balance, eth_balance, sol_balance, trx_balance, bnb_balanceToken balances by chain
total_valueTotal wallet value
Win Rate & Token Stats
winrate, token_sold_avg_profit, history_bought_cost, token_avg_costWin rate and cost metrics
token_num, profit_numTotal tokens and profitable tokens count
pnl_lt_minus_dot5_num, pnl_minus_dot5_0x_num, pnl_lt_2x_num, pnl_2x_5x_num, pnl_gt_5x_numDistribution of token P/L brackets
Profile & Metadata
bind, avatar, name, ens, tags, tag_rankWallet binding and identity data
twitter_name, twitter_username, twitter_bind, twitter_fans_numTwitter profile information
followers_count, is_contract, last_active_timestampActivity and contract status
Risk Metrics
risk.token_active, risk.token_honeypot, risk.token_honeypot_ratio, risk.no_buy_hold, risk.no_buy_hold_ratio, risk.sell_pass_buy, risk.sell_pass_buy_ratio, risk.fast_tx, risk.fast_tx_ratioDetailed risk indicators
Timestamps
avg_holding_period, updated_at, refresh_requested_atHolding period and update timestamps

Example Output

1{
2    "address": "3kebnKw7cPdSkLRfiMEALyZJGZ4wdiSRvmoN4rD1yPzV",
3    "chain": "sol",
4    "period": "7d",
5    "buy": 581,
6    "buy_1d": 115,
7    "buy_7d": 581,
8    "buy_30d": 1322,
9    "sell": 502,
10    "sell_1d": 98,
11    "sell_7d": 502,
12    "sell_30d": 1126,
13    "pnl": -0.10828719023520679,
14    "pnl_1d": 0.03140758753773306,
15    "pnl_7d": -0.10828719023520679,
16    "pnl_30d": -0.08746015532886187,
17    "all_pnl": 0.12871069195157267,
18    "realized_profit": 1684772.7576239784,
19    "realized_profit_1d": 851.1409791878604,
20    "realized_profit_7d": -25207.50269218135,
21    "realized_profit_30d": -45563.020845507424,
22    "unrealized_profit": 4110.971943821579,
23    "unrealized_pnl": 0.00030513736589427,
24    "total_profit": 1688883.7295678,
25    "total_profit_pnl": 0.12877634799199128,
26    "balance": "614.0013232",
27    "eth_balance": "614.0013232",
28    "sol_balance": "614.0013232",
29    "trx_balance": "614.0013232",
30    "bnb_balance": "614.0013232",
31    "total_value": 122227.40625175112,
32    "winrate": 0.4805194805194805,
33    "token_sold_avg_profit": -79.02038461498856,
34    "history_bought_cost": 304309.6197517237,
35    "token_avg_cost": 953.948651259322,
36    "token_num": 319,
37    "profit_num": 148,
38    "pnl_lt_minus_dot5_num": 50,
39    "pnl_minus_dot5_0x_num": 115,
40    "pnl_lt_2x_num": 149,
41    "pnl_2x_5x_num": 5,
42    "pnl_gt_5x_num": 0,
43    "bind": false,
44    "avatar": "https://pbs.twimg.com/profile_images/1913058996174405632/11uKxGds_400x400.jpg",
45    "name": "Bastille",
46    "ens": "",
47    "tags": ["kol", "pump_smart", "photon", "bullx"],
48    "tag_rank": {
49        "bullx": 0,
50        "kol": 1072,
51        "photon": 0,
52        "pump_smart": 35
53    },
54    "twitter_name": "Bastille",
55    "twitter_username": "BastilleBtc",
56    "twitter_bind": false,
57    "twitter_fans_num": 64103,
58    "followers_count": 64103,
59    "is_contract": false,
60    "last_active_timestamp": 1745407556,
61    "risk": {
62        "token_active": 319,
63        "token_honeypot": 0,
64        "token_honeypot_ratio": 0,
65        "no_buy_hold": 7,
66        "no_buy_hold_ratio": 0.02147239263803681,
67        "sell_pass_buy": 2,
68        "sell_pass_buy_ratio": 0.006269592476489028,
69        "fast_tx": 20,
70        "fast_tx_ratio": 0.06269592476489028
71    },
72    "avg_holding_period": 23827.617554858934,
73    "updated_at": 1745407556,
74    "refresh_requested_at": null
75}

Notes: All data is stored in Apify's default dataset.

Pricing

Pricing model

Pay per result 

This Actor is paid per result. You are not charged for the Apify platform usage, but only a fixed price for each dataset of 1,000 items in the Actor outputs.

Price per 1,000 items

$10.00