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Methodology · v1.4.1 · updated 2026-07-04

The agent feed, MCP methodology

A read-only, descriptive cross-exchange microstructure feed exposed over MCP (Model Context Protocol) for AI agents: seven assets across four venues, reported as facts and normalization with no verdicts.

Connect an agent at /agents.

What it is

One MCP call returns one normalized market-state object. The agent feed covers seven assets, BTC, ETH, SOL, BNB, XRP, DOGE, HYPE, across Binance, Bybit, OKX and Hyperliquid, published under the registry name ai.markettrace/agent-feed and hosted at https://api.markettrace.ai/mcp.

The feed reports what it can measure and self-declares how much to trust each number. It never returns a trade recommendation; it reports history and coverage-honest facts. It reports history, not predictions.

Data sources

The feed reuses the same cross-exchange pipeline that powers the site , all-Rust, zero Python daemons. Each metric carries its own provenance and links to a deeper per-metric methodology:

Open interest sums the four venues in native USD, Bybit openInterestValue, OKX oiUsd, Hyperliquid coins × markPx, Binance coins × mark. oi.rel compares the current value against its trailing hourly median (1d / 1w / 1m), and oi.chg_1h_pct is the change over the previous complete hour. The baseline joins on the live venue set, so legacy Binance-only rows drop out of the median, an honest re-accrual rather than a silent blend of old and new coverage.

volume.usd_24h is the consolidated 24-hour traded notional across venues; volume.rel expresses that against its trailing hourly median, as a multiplier.

price.last is the consolidated mid. The chg_*_pct fields are returns versus a tolerance-matched baseline; atr_1h_pct is ATR(14) on hourly bars, as a percent of price; and rv_24h_pct is realized volatility annualized from minute returns.

Coverage honesty

Every metric carries a coverage entry. A thin or young metric is answered honestly, with its depth disclosed, and is never faked to look deep.

coverage: { venues, window_days, n_samples, partial, reason }
reason ∈ { accruing | unavailable | degraded | stale }

age_seconds is the worst-case age across the live sources that fed the non-null fields, so a single stale sub-feed cannot hide behind fresher ones. A feed beacon on every response , feed.version and feed.tools, lets an agent detect a stale, cached tool catalog and re-read the schema.

Conditional outcomes

The flagship tool measures base rates of forward returns after a caller-stated condition. It replaces folklore, “high funding means a squeeze”, with the base rate drawn from the feed's own data. The mechanics are deliberately conservative:

r_h(t)  = close(t+h) / close(t) − 1            // forward return at horizon h
maxDD_h = min( low(t+1 … t+h) ) / close(t) − 1  // worst hourly low in (t, t+h]

State history

A 15-minute archive stores the full served market-state per asset. get_state_history returns parallel time-series arrays of any numeric dotted field, funding.percentile, oi.usd, obi.skew, downsampled to max_points. The stride used is reported, and the newest row is never sampled away. The archive is young, it was born 2026-07-03, and grows forward, so thin answers are honest, not broken.

Tools

For how to connect an agent, see /agents.

Limitations

Versioning

Methodology version v1.4.1 · updated 2026-07-04. Material changes (new sources, formula tweaks, threshold changes) bump the version and update dateModified in the structured data above.

v1.4.1 (2026-07-04): first published methodology for the MCP agent feed, the coverage-honesty model, conditional-outcomes statistics, and the 15-minute state archive.