Trust Updated 2026-08-01 View as Markdown

Changelog

Platform changes that affect what you can do. Internal refactors, performance work and dependency updates are not listed.

August 2026 — MCP server

External AI clients can now read your record.

MCP server at POST /api/mcp, stateless JSON-RPC over HTTP, with sixteen read-only tools. Claude Code, Claude Desktop and Cursor all connect directly. See MCP server.
Warehouse tools — six tools available only over MCP that return raw analytical evidence rather than a precomputed verdict: the daily feature matrix, the correlation graph as structured edges, all-time facts, statistical models and narrative summaries. These let a client test a hypothesis the nightly engine never considered.
API tokens — revocable machine credentials with explicit read and write scopes, stored as hashes, managed with the token scripts.
This documentation site, with the tool and metric references generated directly from source so they cannot drift.

Unified correlation engine spanning habits, nutrition, WHOOP, bloodwork and genetics in one graph, with partial-correlation controls, autocorrelation-adjusted significance and multiple-testing correction.
On-demand relationship analysis for any two metrics, applying the same statistical guards, always labelled a hypothesis.
Insights engine — readiness scoring, lead-lag detection, goal ETA with Monte Carlo confidence bands, streak survival curves, training load, HRV baseline, dose-response curves, changepoint detection.
User fact index derived from the metric registry, which fixed a real class of error: personal records that only reflected the most recent thirty days.
Metric registry as the single source of truth for metric semantics, replacing definitions that had been copy-pasted across five modules and drifted apart.

Bloodwork. Upload lab PDFs, extract markers, track trends against reference ranges, correlate against daily behaviour over biologically plausible windows.
Methylation genetics. One-time genetic profile with pathway view, clusters, genetically predicted watch markers cross-linked to your labs, and priors that get tested rather than asserted.
WHOOP webhooks, so recovery scores appear within minutes instead of at the next scheduled pull.
Data-quality gating for WHOOP calibration periods and nights with sensor gaps — visible in the ledger, excluded from analysis.
Mission Statement — one goal, three commitments, with progress and causality analysis.

Context Engine 2.0 — temporal awareness, momentum detection, lifecycle stage, profile gap discovery.
Smart payload — question classification driving model choice, reasoning effort and context size.
Learnings system — bidirectional extraction, semantic deduplication, decay, consolidation, bounded storage.
Voice agent over a realtime speech model, with unified, chat, data-entry and onboarding modes.
Prompt injection defense on the AI endpoints.
Hybrid retrieval — vector search and full-text search fused and reranked.