Hyperliquid Market Data — OHLCV, Funding Rates & Positioning (Tessera)

Hyperliquid perp market data for LLMs: OHLCV, funding, open interest, positioning & forecasts.

Community: Submitted by a user or imported; check the owner before granting accessOnlineAPI key requiredGlobalFreeRead-only

What it can do

    What data it sees

    Do you need an account

    An API key from the service settings is required

    Hyperliquid perp market data for LLMs: OHLCV, funding, open interest, positioning & forecasts.

    How to connect

    How to connect Hyperliquid Market Data — OHLCV, Funding Rates & Positioning (Tessera) to Claude

    The server address to paste into Claude settings:

    https://tesseralytics.dev/mcp

    1. Open Claude (claude.ai or the desktop app).
    2. Go to Settings → Connectors.
    3. Click Add custom connector.
    4. Paste the server address copied below into Remote MCP server URL and click Add.
    5. In a chat, click + → Connectors and switch the new connector on.

    Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

    Authorization

    After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

    How to connect Hyperliquid Market Data — OHLCV, Funding Rates & Positioning (Tessera) to ChatGPT

    The server address to paste into ChatGPT settings:

    https://tesseralytics.dev/mcp

    1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
    2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
    3. Open Settings → Connectors and click Create.
    4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
    5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
    6. In a new chat open + → Apps/Connectors and enable the connector.

    OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

    Authorization

    On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

    How to connect Hyperliquid Market Data — OHLCV, Funding Rates & Positioning (Tessera) to Cursor

    The server address to paste into Cursor settings:

    https://tesseralytics.dev/mcp

    Fastest: click Open in Cursor below and confirm the prompt.

    Manually:

    1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
    2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
    3. Save the file. The server appears in the MCP list; authorize it there if asked.

    Authorization

    If the service needs sign-in, an authorize button appears next to the server in the MCP list.

    Server tool list (9)

    Raw names from tools/list. Only developers need these.

    list_fieldsEvery field the query tools accept, each with its meaning, unit and whether it can be missing. Open — no key needed. Call this before query_cross_section, screen_universe or query_series. Percentile, z-score and the top_pct/bottom_pct conditions rank within the markets your plan can see, so they need a wide slice.
    get_universeThe coverage picture: the last complete day, how many markets are in the universe for a scope, how much history sits behind them, and how densely it is populated. A compact SUMMARY by default — pass top_n (1..50) only if you need the per-market day counts.
    describe_datasetThe full dictionary for ONE downloadable dataset: description plus every column's type, nullability and plain-English meaning. Pass a name from list_datasets. Open — no key needed. For the fields the query tools accept, use list_fields.
    query_cross_sectionRank the whole market on ONE completed day: pick columns, an order_by field and top_n. Answers 'top markets by funding / open interest / returns on the latest day' and 'what percentile is BTC on open interest'. day defaults to the last complete day; scope defaults to crypto (HIP-3 markets track an underlying that closes, so their flow is not comparable); stat=percentile|zscore ranks within your visible markets; window_days recomputes the trailing-window fields; min_usd_volume_7d_avg keeps dust out of the ranking.
    list_datasetsList the downloadable datasets: one-line summary, the plan required, and the month range available. Open — no key needed. Then use describe_dataset for one dataset's columns, or list_fields for the fields the query tools accept.
    screen_universeScreen the whole market on ONE completed day with several conditions ANDed together. Conditions use op >, <, >=, <=, between, top_pct or bottom_pct; top_pct/bottom_pct are deciles of the markets you can see. Answers 'top-decile funding with bottom-decile open-interest change' and 'open interest rising faster than volume'. A market that does not report a field never satisfies a condition on it.
    live_marketWhat is happening right now: mark price, current hourly funding, open interest, 24-hour traded notional and premium for up to 25 markets, taken straight from the venue's public API and stamped with the moment it was read. Use this for 'now' questions; the daily tools answer completed days only.
    query_seriesThe daily series for one market or a few (max 10): one row per market per day over a trailing window, oldest first. Answers 'is this move backed by real flow' and 'how has positioning built up'. ending_day defaults to the last complete day. The whole answer is capped, so markets times window_days must stay inside the row cap; the response states the window it used.
    funding_divergenceRank markets by how far their funding has diverged from a benchmark (default ETH) over a trailing window. metric=rate compares mean daily funding; metric=cum_funding_spread compares funding accumulated over the window. Returns the most diverged in each direction. Markets with no funding reading are excluded from both lists. Descriptive only.