Hyperliquid · Stats

Hyperliquid stats: daily volume, open interest and perps analytics

Hyperliquid's perps volume hour by hour, for the venue or one coin, open interest per coin beside the venue's own figure, and equity and position counts over time: the numbers behind any Hyperliquid dashboard, over MCP, REST and the CLI.

Ask your AI · Claude, ChatGPT, CursorConnect in a minute →

“What were Hyperliquid's perps volume and open interest each day this week?”

hl_stats

“Which coins carry the most open interest on Hyperliquid right now?”

hl_market

Live

Hyperliquid stats right now

The venue's equity, open interest and positions at the newest hour, and open interest per coin at the latest 5-minute snapshot: real answers of the API, captured on a schedule.

Venue stats · /stats

GET/v1/hyperliquid/stats

Open this side to see the captured response.

Open interest per coin · /positions/symbols

GET/v1/hyperliquid/positions/symbols

Open this side to see the captured response.

On vike.io · free, no key

Open interest and funding, on vike.io

Funding rate and open interest per perp, hourly over 1, 7 or 30 days, beside limit-order absorption: how much market buying and selling resting limit orders soaked up.

Open order flow →

Stats API

Volume, open interest and venue stats over time

Hour by hour, for the whole venue or one coin. Volume is the traded notional counted once per trade (one side), the figure the candles report; until 2026-10-25 it counted both sides of every trade and was exactly twice that.

Ask your AI: hl_stats (views ecosystem, volume; 1 credit a call) and hl_market (view open_interest; 1 credit a call). Connect Claude, ChatGPT or Cursor: AI & API →

Hyperliquid · REST · CLI · MCP

Perps volume per hour, the whole venue or one coin

Route: GET /v1/hyperliquid/stats/volume
CLI: vike-data hl stats
MCP: hl_stats · 1 credit
Cost: 1 request of the hourly limit

Free APIArchiveStreamMCP

Hourly perp volume, whole venue or one coin.

volume is the traded notional counted once per trade (one side), the figure the candles report; until 2026-10-25 it counted both sides of every trade and was exactly twice that. The venue total (no symbol) is perp volume, builder-dex perps included, and leaves out spot and outcome markets; naming one of those as symbol still returns it. n_fills counts fill records, two per trade (one for each side).

Parameters

Parameter	In	Description
`symbol`	query	HL ticker. Omit for the whole venue
`start`	query	ISO-8601 UTC bounds
`end`	query	ISO-8601 UTC bounds
`limit`	query	Default 500, max 5000
`cursor`	query	Keyset cursor

Call it

bash

curl -H "X-API-KEY: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hyperliquid/stats/volume?limit=168"

python

import os
from collections import defaultdict

import requests

r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats/volume",
    params={"limit": 168},     # the last 168 hours of the whole venue, newest first
    headers={"X-API-KEY": os.environ["VIKE_API_KEY"]},
).json()
daily = defaultdict(float)
for h in r["volume"]:
    daily[h["ts"][:10]] += h["volume"]     # each trade counted once
for day, usd in sorted(daily.items()):     # the first and the last day are partial
    print(day, f"${usd:,.0f}")

bash

vike-data hl stats --view volume --limit 168

bash

# any MCP client; or from the terminal:
vike-data call hl_stats --args '{"view": "volume", "limit": 168}'

Hyperliquid · REST · CLI · MCP

Equity, open interest and positions of the whole venue, hour by hour

Route: GET /v1/hyperliquid/stats
CLI: vike-data hl stats
MCP: hl_stats · 1 credit
Cost: 1 request of the hourly limit

Free APIArchiveStreamMCP

Ecosystem time series: perp equity, open interest, position counts.

Parameters

Parameter	In	Description
`start`	query	ISO-8601 UTC bounds
`end`	query	ISO-8601 UTC bounds
`limit`	query	Default 500, max 5000
`cursor`	query	Keyset cursor

Call it

bash

curl -H "X-API-KEY: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hyperliquid/stats?limit=168"

python

import os, requests

r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats?limit=168",
    headers={"X-API-KEY": os.environ["VIKE_API_KEY"]},
)
print(r.json())

bash

vike-data hl stats --limit 168

bash

# any MCP client; or from the terminal:
vike-data call hl_stats --args '{"view": "ecosystem", "limit": 168}'

Hyperliquid · REST · CLI · MCP

Open interest per coin, beside the venue's own figure

Route: GET /v1/hyperliquid/positions/symbols
CLI: vike-data hl market
MCP: hl_market · 1 credit
Cost: 1 request of the hourly limit

Free APIArchiveStreamMCP

Market-wide open interest per coin at the latest snapshot, with the venue's own OI alongside our aggregate so the two can be reconciled.

Parameters

None.

Call it

bash

curl -H "X-API-KEY: $VIKE_API_KEY" \
  "https://data.vike.io/v1/hyperliquid/positions/symbols"

python

import os

import requests

coins = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-KEY": os.environ["VIKE_API_KEY"]},
).json()
for c in coins[:10]:     # the most open interest first
    print(c["symbol"], f"${c['total_value']:,.0f}", "venue:", c["venue_open_interest_usd"])

bash

vike-data hl market --view open_interest

bash

# any MCP client; or from the terminal:
vike-data call hl_market --args '{"view": "open_interest"}'

Studies

13 studies

Each with the sentence to ask your AI instead. Every block was run against the live API on 2026-11-03.

Hyperliquid · API

Hyperliquid exchange-wide daily volume, trades and users

Roll the hourly venue-wide volume and fill counts of /v1/hyperliquid/stats/volume up into days (volume counts each trade once; halve the fill count for trades); daily distinct traders are not served by the API and come from the fills archive.

Uses: /ohlcv, /stats, /stats/volume
Verified: live API, 2026-11-03: 6 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “What was Hyperliquid's total perp volume per day over the last week?”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the last 7 days of venue-wide volume and trades, by UTC day, counting each trade once
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats/volume?limit=168",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.volume | group_by(.ts[:10]) | map({day: .[0].ts[:10], hours: length, volume_usd: (map(.volume) | add), trades: ((map(.n_fills) | add) / 2 | floor)})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# BTC volume and fills by the hour
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats/volume?symbol=BTC&limit=3",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the hourly BTC candles for the same hours; volume_usd and n_trades count each trade once
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=BTC&interval=1h&limit=4",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# venue-wide equity, open interest and position counts, newest hours first
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats?limit=3",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the 168 hours before the first page's last hour; NEXT is its nextCursor, passed back verbatim
first = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats/volume?limit=168",
    headers={"X-API-Key": API_KEY},
).json()
NEXT = first["nextCursor"]
r = requests.get(
    f"https://data.vike.io/v1/hyperliquid/stats/volume?limit=168&cursor={NEXT}",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

How healthy is Hyperliquid: total perp equity, open interest and OI-to-equity over time?

One row per hour of total perp equity, open interest and position counts, from /v1/hyperliquid/stats; divide open_interest by total_perp_equity for the ratio.

Uses: /positions/symbols, /stats
Verified: live API, 2026-11-03: 6 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “How have Hyperliquid's total perp equity and open interest moved over the last 30 days?”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the last 30 days, one row per hour, newest first
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats?limit=720",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# every hour of September 2026
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats?start=2026-09-01T00:00:00Z&end=2026-09-30T23:59:59Z&limit=720",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# OI-to-equity and the share of positions in profit, hour by hour
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats?limit=168",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.metrics[] | {ts, oi_to_equity: (.open_interest / .total_perp_equity), in_profit: (.count_positions_in_profit / .count_open_positions)}'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# NEXT is the first page's nextCursor: the 720 hours before the last row it returned
first = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats?limit=720",
    headers={"X-API-Key": API_KEY},
).json()
NEXT = first["nextCursor"]
r = requests.get(
    f"https://data.vike.io/v1/hyperliquid/stats?limit=720&cursor={NEXT}",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# open interest per coin now, with the venue's published open interest beside it
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

Hyperliquid open interest per coin, and how it reconciles with the venue

Open interest of every Hyperliquid coin summed from open positions, with the venue's own figure beside it.

Uses: /positions/symbols, /v1/hl-cohorts/symbols/{…}/metrics
Verified: live API, 2026-11-03: 5 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “What is the open interest of each Hyperliquid coin right now, and does it match the venue's own figure?”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# open interest of every coin at the latest snapshot, biggest first
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the ten coins with the most open interest, with position counts
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.[:10] | map({symbol, total_value, count})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# our aggregate over the venue's published open interest, per coin
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.[] | select(.venue_open_interest_usd != null) | {symbol, ratio: (.total_value / .venue_open_interest_usd)}'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the share of open positions that are longs, per coin
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.[:20] | map({symbol, long_share: (.count_long / .count)})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# BTC open interest and position count, one row per hour for a week
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/BTC/metrics?limit=168",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

Hourly open interest and position count history of a Hyperliquid coin

One row per hour with position_count, long count, long and total notional in USD and bias, from /v1/hl-cohorts/symbols/{symbol}/metrics; /v1/hyperliquid/symbols/hourly adds the venue's own open interest per hour.

Uses: /symbols/hourly, /v1/hl-cohorts/symbols/{…}/metrics
Verified: live API, 2026-11-03: 5 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “Show the hourly open interest and position count of BTC on Hyperliquid for the last 24 hours”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the newest hourly rows for BTC; the first row is the hour still in progress
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/BTC/metrics?limit=3",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# BTC hourly close, open interest, funding rate and premium for the last day
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/symbols/hourly?symbols=BTC&days=1",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# one week of hourly BTC rows
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/BTC/metrics?start=2026-10-10T00:00:00Z&end=2026-10-16T23:59:59Z&limit=168",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# hourly BTC positioning of positions opened within the previous 24 hours
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/BTC/metrics?openedWithin=24h&limit=48",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# hourly positioning in the XYZ platinum perp
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/xyz:PLATINUM/metrics?limit=24",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

How is a Hyperliquid coin's open interest split by position size and by account size?

Split one coin's open positions into ten position-size buckets with /v1/hl-cohorts/symbols/{symbol}/size-breakdown; /cohort-metrics?axis=size splits the same book by the size of each wallet's account.

Uses: /v1/hl-cohorts/segments, /v1/hl-cohorts/symbols/{…}/cohort-metrics, /v1/hl-cohorts/symbols/{…}/size-breakdown
Verified: live API, 2026-11-03: 4 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “How is BTC open interest on Hyperliquid split by position size?”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# BTC open positions in ten position-size buckets, largest first
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/BTC/size-breakdown",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# BTC positioning per account-size tier, newest settled hour
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/BTC/cohort-metrics?axis=size&hours=1",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# one week of BTC positioning per position-size bucket
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/BTC/cohort-metrics?axis=tier&hours=168",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# every cohort ladder with its bounds
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/segments",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

How concentrated is Hyperliquid open interest? Top-10 wallets' share of BTC OI

Sum size_usd of the 10 rows from /v1/hyperliquid/positions?symbol=BTC&sort=size&limit=10 and divide by BTC's total_value from /v1/hyperliquid/positions/symbols.

Uses: /archive/url, /positions, /positions/symbols
Verified: live API, 2026-11-03: 5 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “What share of BTC open interest on Hyperliquid do the 10 biggest positions hold right now?”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the 10 biggest open BTC positions, largest first
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions?symbol=BTC&sort=size&limit=10",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# open interest per coin; take the BTC row
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.[] | select(.symbol == "BTC")'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the 100 biggest open BTC positions, for a top-100 share
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions?symbol=BTC&sort=size&limit=100",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the top-10 notional and its split by side, to divide by BTC's total_value
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions?symbol=BTC&sort=size&limit=10",
    headers={"X-API-Key": API_KEY},
)
# then: jq '{top10_usd: ([.positions[].size_usd] | add), longs_usd: ([.positions[] | select(.direction == "long") | .size_usd] | add), shorts_usd: ([.positions[] | select(.direction == "short") | .size_usd] | add)}'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# a temporary link to the current open positions of every asset, refreshed about every 5 minutes
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/archive/url?dataset=positions&date=latest",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

Count distinct wallets per UTC day in the archive's daily fills files, and per wallet the share of its notional filled as maker; the API itself does not serve a daily active-traders count.

Uses: /archive/url, /stats
Verified: live API, 2026-11-03: 2 calls, all 200

Free APIArchiveStreamMCP

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# download one UTC day of every fill; repeat per day
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/archive/url?dataset=fills&date=2026-10-23&redirect=1",
    headers={"X-API-Key": API_KEY},
)
with open("fills-2026-10-23.parquet", "wb") as f:
    f.write(r.content)

python

import polars as pl

per_wallet = (
    pl.scan_parquet("fills-2026-10-*.parquet")  # every day you downloaded, read as one table
    .group_by(pl.col("fill_ts").dt.date().alias("day"), "wallet")
    .agg(usd=pl.col("size_usd").sum(), maker_usd=pl.col("size_usd").filter(pl.col("is_maker")).sum())
)
daily = (
    per_wallet.group_by("day")
    .agg(
        active_wallets=pl.len(),
        with_a_maker_fill=(pl.col("maker_usd") > 0).sum(),
        mostly_maker=(pl.col("maker_usd") > 0.5 * pl.col("usd")).sum(),
    )
    .sort("day")
    .collect()
)
print(daily)

python

import polars as pl

first = (
    pl.scan_parquet("fills-2026-*.parquet")
    .group_by("wallet").agg(first_day=pl.col("fill_ts").min().dt.date())
    .group_by("first_day").agg(new_wallets=pl.len())
    .sort("first_day")
    .collect()
)

python

import polars as pl

per_coin = (
    pl.scan_parquet("fills-2026-10-*.parquet")
    .group_by(pl.col("fill_ts").dt.date().alias("day"), "asset")
    .agg(active_wallets=pl.col("wallet").n_unique())
    .sort("day", "active_wallets", descending=[False, True])
    .collect()
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# venue-wide hourly equity, open interest and account counts
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/stats?limit=24",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

List every Hyperliquid instrument that traded in the last hour, including HIP-3 dexes and spot

One row for every perp that traded in the last 60 minutes on every dex, each naming its dex, from /v1/hyperliquid/ohlcv/latest without dex; market=spot does the same for spot pairs.

Uses: /ohlcv/latest
Verified: live API, 2026-11-03: 4 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “List every Hyperliquid instrument that traded in the last hour, HIP-3 dexes included”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# every perp that traded in the last hour, on every dex, one row each
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# every spot pair that traded in the last hour
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest?market=spot",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# how many instruments traded in the last hour on each dex
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.candles | group_by(.dex) | map({dex: .[0].dex, instruments: length})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# only the markets of the PARA dex
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest?dex=PARA",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

Screen all Hyperliquid coins for the biggest 1-minute move right now

One call to /v1/hyperliquid/ohlcv/latest returns the newest 1-minute candle of every perp that traded in the last hour; rank them by (close - open) / open, or by volume_usd for the most traded coins.

Uses: /ohlcv, /ohlcv/latest
Verified: live API, 2026-11-03: 4 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “Which Hyperliquid coin moved the most in the last minute? Then show me its last 60 one-minute candles”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the five biggest 1-minute moves among coins with at least 20 trades in their newest minute
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest",
    headers={"X-API-Key": API_KEY},
)
# then: jq '(.candles | map(.ts) | max) as $t | [.candles[] | select(.ts >= $t - 60000 and .n_trades >= 20 and (.symbol | startswith("#") | not)) | {symbol, dex, ts, open, close, n_trades, move_pct: ((.close - .open) / .open * 100)}] | sort_by(-(.move_pct | fabs)) | .[:5]'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the five coins with the most USD traded in their newest minute
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest",
    headers={"X-API-Key": API_KEY},
)
# then: jq '(.candles | map(.ts) | max) as $t | [.candles[] | select(.ts >= $t - 60000 and (.symbol | startswith("#") | not)) | {symbol, dex, ts, volume_usd, n_trades}] | sort_by(-.volume_usd) | .[:5]'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the newest candle of every XYZ market
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest?dex=XYZ",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the last 60 one-minute ANIME candles
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=ANIME&interval=1m&limit=60",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

Which HIP-3 builder dex is busiest this minute?

Call /v1/hyperliquid/ohlcv/latest without dex, keep the rows of the newest minute, and sum volume_usd and n_trades per dex; each row names its own dex.

Uses: /ohlcv, /ohlcv/latest
Verified: live API, 2026-11-03: 4 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “Which HIP-3 builder dex on Hyperliquid traded the most in the last minute?”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# USD traded, trades and active symbols per dex in the newest minute
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest",
    headers={"X-API-Key": API_KEY},
)
# then: jq '(.candles | map(.ts) | max) as $t | [.candles[] | select(.ts == $t and (.symbol | startswith("#") | not))] | group_by(.dex) | map({dex: .[0].dex, symbols: length, volume_usd: (map(.volume_usd) | add), n_trades: (map(.n_trades) | add)}) | sort_by(-.volume_usd)'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the newest candle of every XYZ market, most USD first
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest?dex=XYZ",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.candles | sort_by(-.volume_usd) | .[:5] | map({symbol, ts, volume_usd, n_trades})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# symbols per dex that traded in the last 60 minutes
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest",
    headers={"X-API-Key": API_KEY},
)
# then: jq '[.candles[] | select(.symbol | startswith("#") | not)] | group_by(.dex) | map({dex: .[0].dex, symbols: length})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# 24 hourly candles of one XYZ market
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=xyz:MRNA&dex=XYZ&interval=1h&limit=24",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

HIP-3 stock perps on Hyperliquid: candles, volume, and who trades them

Candles, volume, biggest holders and recent large fills of a HIP-3 stock perp such as xyz:TSLA.

Uses: /builders/{…}/fills, /ohlcv, /ohlcv/latest, /positions, /v1/hl-cohorts/symbols/{…}/large-fills
Verified: live API, 2026-11-03: 5 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “Show the daily candles of xyz:TSLA on the XYZ dex for the last week”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# a week of daily xyz:TSLA candles, whole UTC days
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=xyz:TSLA&dex=XYZ&interval=1d&start=2026-10-17T00:00:00Z&end=2026-10-24T00:00:00Z",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the 20 biggest open xyz:TSLA positions, largest first
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions?symbol=xyz:TSLA&sort=size&limit=20",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# xyz:TSLA fills over $50,000 in the last 24 hours
r = requests.get(
    "https://data.vike.io/v1/hl-cohorts/symbols/xyz:TSLA/large-fills",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the newest 1-minute candle of every XYZ market that traded in the last hour
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest?dex=XYZ",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the newest xyz:TSLA fills routed through one builder code
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/builders/0xb84168cf3be63c6b8dad05ff5d755e97432ff80b/fills?symbol=xyz:TSLA&limit=100",
    headers={"X-API-Key": API_KEY},
)

Hyperliquid · API

Which Hyperliquid tokens trade more on spot than on perp?

For a token you name, sum volume_usd from /v1/hyperliquid/ohlcv with market=spot and from the perp over the same hours; spot rows carry a spot index (@107), not a name, so a screen of every token needs the names first.

Uses: /ohlcv, /ohlcv/latest
Verified: live API, 2026-11-03: 5 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “Compare HYPE spot and HYPE perp volume on Hyperliquid over the last 24 hours”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# HYPE spot: USD traded over the last 24 hourly candles
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=HYPE&market=spot&interval=1h&limit=24",
    headers={"X-API-Key": API_KEY},
)
# then: jq '{symbol, volume_usd: ([.candles[].volume_usd] | add)}'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# HYPE perp: the same 24 hours
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=HYPE&interval=1h&limit=24",
    headers={"X-API-Key": API_KEY},
)
# then: jq '{symbol, volume_usd: ([.candles[].volume_usd] | add)}'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the newest 1-minute candle of every spot pair, most USD first
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest?market=spot",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.candles | sort_by(-.volume_usd) | .[:5] | map({symbol, ts, volume_usd, n_trades})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# HYPE resolves to @107
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=HYPE&market=spot&interval=1d&limit=1",
    headers={"X-API-Key": API_KEY},
)
# then: jq -r '.symbol'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# HYPE spot, 168 hourly candles; repeat without market=spot for the perp
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=HYPE&market=spot&interval=1h&limit=168",
    headers={"X-API-Key": API_KEY},
)
# then: jq '[.candles[].volume_usd] | add'

Hyperliquid · API

Pick a tradable universe: the most liquid, most volatile or largest-OI Hyperliquid perps

Rank coins by open interest from /v1/hyperliquid/positions/symbols, then measure volatility from hourly closes on /v1/hyperliquid/symbols/hourly and daily volume from /v1/hyperliquid/ohlcv.

Uses: /ohlcv, /ohlcv/latest, /positions/symbols, /symbols/hourly
Verified: live API, 2026-11-03: 4 calls, all 200

Free APIArchiveStreamMCP

Ask your AI agent: “List the 30 Hyperliquid perps with the most open interest right now”

The code

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the 30 coins with the most open interest
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/positions/symbols",
    headers={"X-API-Key": API_KEY},
)
# then: jq '.[:30] | map({symbol, total_value, count})'

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# hourly closes of a basket over 30 days, one row per coin-hour
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/symbols/hourly?symbols=BTC,ETH,HYPE,SOL,ZEC&days=30",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# BTC's traded notional on 2026-10-23
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv?symbol=BTC&interval=1d&start=2026-10-23T00:00:00Z&end=2026-10-24T00:00:00Z",
    headers={"X-API-Key": API_KEY},
)

python

import os
import requests

API_KEY = os.environ["VIKE_API_KEY"]  # your key, read from the environment

# the newest 1-minute candle of every coin that traded in the last hour
r = requests.get(
    "https://data.vike.io/v1/hyperliquid/ohlcv/latest",
    headers={"X-API-Key": API_KEY},
)

FAQ

Hyperliquid stats FAQ

What is Hyperliquid's daily volume?

Sum the hourly rows of GET /v1/hyperliquid/stats/volume per UTC day: volume is the traded notional counted once per trade (one side), the figure the candles report; until 2026-10-25 it counted both sides of every trade and was exactly twice that. n_fills counts fill records, two per trade. The venue total is perp volume, builder-dex perps included, without spot and outcome markets.

How do I get Hyperliquid open interest per coin?

GET /v1/hyperliquid/positions/symbols gives every coin's open interest summed from open positions at the latest snapshot, longs and shorts apart, with the venue's own figure beside it so the two reconcile. Over MCP: hl_market with view open_interest.

Is there a free Hyperliquid stats API?

Yes: /stats, /stats/volume and /positions/symbols, the MCP tool hl_stats for Claude or ChatGPT and the CLI command vike-data hl stats, on one free key, 20,000 requests an hour.

Can I build my own Hyperliquid dashboard?

Yes. /stats gives total perp equity, open interest and position counts per hour, /stats/volume the volume per hour, /positions/symbols open interest per coin now, and the studies below turn them into daily series, ratios and screens.

Does the API give daily active traders?

Not as a route: count distinct wallets per day in the fills archive, one Parquet file a day, as the study on active traders does.

Hyperliquid stats right now

Venue stats · /stats

Open interest per coin · /positions/symbols

Open interest and funding, on vike.io

Volume, open interest and venue stats over time

Perps volume per hour, the whole venue or one coin

Parameters

Call it

Equity, open interest and positions of the whole venue, hour by hour

Parameters

Call it

Open interest per coin, beside the venue's own figure

Parameters

Call it

13 studies

Hyperliquid exchange-wide daily volume, trades and users

The code

How healthy is Hyperliquid: total perp equity, open interest and OI-to-equity over time?

The code

Hyperliquid open interest per coin, and how it reconciles with the venue

The code

Hourly open interest and position count history of a Hyperliquid coin

The code

How is a Hyperliquid coin's open interest split by position size and by account size?

The code

How concentrated is Hyperliquid open interest? Top-10 wallets' share of BTC OI

The code

How many traders were active on Hyperliquid each day, and what share were makers?

The code

List every Hyperliquid instrument that traded in the last hour, including HIP-3 dexes and spot

The code

Screen all Hyperliquid coins for the biggest 1-minute move right now

The code

Which HIP-3 builder dex is busiest this minute?

The code

HIP-3 stock perps on Hyperliquid: candles, volume, and who trades them

The code

Which Hyperliquid tokens trade more on spot than on perp?

The code

Pick a tradable universe: the most liquid, most volatile or largest-OI Hyperliquid perps

The code

Hyperliquid stats FAQ