Tessera Analytics - Hyperliquid Market Intelligence

npx add-mcp 'https://tesseralytics.dev/mcp'

Hyperliquid intelligence, built for trading agents.

The intelligence layer is our MCP server: rank the whole market in one call — crowded funding, funding divergence, decile screens — over order-flow-enriched Hyperliquid data. Nine tools for your agent; REST and Parquet for everything else.

No card required — the free tier is order-flow-enriched minute OHLCV for BTC, ETH, SOL & HYPE over the trailing month.

tessera.mcp · claude query_cross_section · ok

youWhich markets’ longs are paying the most to hold?

query_cross_section({ day: "2026-09-15", order_by: "funding_rate_mean", top_n: 6 })

One call. No download code, no files, no aggregation in the prompt — the intelligence layer ranks the cross-section and returns 6 rows.

33 of 234 markets ranked as of 2026-09-15

#CoinFunding /hAnnualised

1 USELESS +0.00204% +17.9%

2 VVV +0.00189% +16.6%

3 CASHCAT +0.00182% +16.0%

4 PONS +0.00170% +14.9%

5 LIT +0.00125% +10.9%

6 ENA +0.00125% +10.9%

Real Hyperliquid funding history, complete UTC day 2026-09-15 — the mean of the day’s 24 hourly rates, captured 2026-09-16.

One question, two shapes

A row API hands the model fills — one row each, millions a day — and leaves the aggregation to it. The intelligence layer ranks the cross-section and returns the answer.

GET /v1/trades?coin=BTC raw rows

• {"px":75744.0,"sz":0.00345,"side":"B","time":1789566701384}
• {"px":75743.0,"sz":0.00037,"side":"B","time":1789566701384}
• {"px":75743.0,"sz":0.00015,"side":"B","time":1789566701384}
• {"px":75743.0,"sz":0.00017,"side":"B","time":1789566701384}
• {"px":75743.0,"sz":0.00017,"side":"B","time":1789566701384}
• {"px":75743.0,"sz":0.0002,"side":"B","time":1789566701384}
• {"px":75743.0,"sz":0.00032,"side":"B","time":1789566700697}
• {"px":75742.0,"sz":0.00016,"side":"A","time":1789566700507}
• {"px":75743.0,"sz":0.00227,"side":"B","time":1789566699555}
• {"px":75743.0,"sz":0.00017,"side":"B","time":1789566699555}

10 consecutive BTC prints. The market’s shape is still yours to compute.

screen_universe 3 of 33 matched

screen_universe({ day: "2026-09-15", conditions: [ { field: "funding_rate_mean", op: ">=", value: 0.000015 }, { field: "ret_1d", op: "<", value: 0 } ] })

Longs paying most, price falling as of 2026-09-15

#CoinFunding /hDay

1 VVV +0.00189% −-7.83%

2 CASHCAT +0.00182% −-2.25%

3 PONS +0.00170% −-2.16%

Two conditions, one call, 33 markets screened — computed here from the same captured day.

The market, then the numbers behind it

Both paths serve the same three gold datasets, rebuilt every night from the raw Hyperliquid tape: order-flow-enriched minute OHLCV with CVD, hourly funding with cumulative carry, hourly positioning with whale net position.

Two paths to the same lake

The intelligence layer and the API read identical Parquet. Pick whichever suits your use case: raw Parquet for backtests, the intelligence layer for live trading agents.

A hosted MCP server at one endpoint: rank the cross-section, screen on several conditions, measure funding divergence, pull a per-coin series, read the live market. No download code and no local files — the model calls a tool and reasons over the answer.

claude mcp add --transport http tessera https://tesseralytics.dev/mcp \
  --header "Authorization: Bearer $TESSERA_API_KEY"

Auth is the API key you already have. Discovery tools work without one. See the tool reference →

Every partition is a plain Parquet file behind a presigned URL, or one call from the Python SDK straight into Polars or DuckDB SQL. Drop it into a backtester; there’s no per-GB fee.

df = client.read("gold_ohlcv_1m", "BTC", "2026-05")

GET /v1/datasets lists what your key can reach. See the SDKs →

Tessera is Latin for a small tile — one piece of a larger picture. Two large tiles and the small ones beneath them: the intelligence layer and the REST API are the ways in, and every dataset is a tile of the market behind them.