Docs.
Everything here is mirrored in markdown — append .md to any URL or send Accept: text/markdown. Index for agents: /llms.txt
# remote — Streamable HTTP, OAuth 2.1\nhttps://hunter-seeker.net/api/mcpQuickstart
Target: first successful call in under five minutes. No signup needed for the demo tenant.
# 1 · connect (remote MCP)\nhttps://hunter-seeker.net/api/mcp# 2 · paste into your agent\nConnect to the Hunter-Seeker MCP server, call hs_describe_capabilities,\nthen rank the demo churn dataset by likelihood of churn and return the\ntop 10 with evidence and provenance.Free tier: the full 8-tool surface, 3 runs/month on your own data, unlimited demo tenant. Per-client install for Cursor, Claude, VS Code, LangChain and CrewAI is on the agents page.
MCP server
Eight tools — one costs a run, seven are free reuse — with at most eight natural-language parameters each, typed errors, idempotency, and the trust contract in every envelope. The server fronts the product layer only, never the engine.
Input contract, problem shapes, trust guarantees, and worked multi-domain examples. Call first when unsure.
Register tabular data past the inline cap. Presigned upload or guarded https fetch (public hosts only). direct_upload streams a large dataset (up to ~1M rows) straight to storage, past the proxy body cap.
Rank rows by likelihood of a yes/no outcome; top-k with calibrated scores, top_factors, lift, gate verdicts, leak-guard, provenance.
Poll a pending async run. Returns pending — optionally with a leak-firewalled stage and facts_so_far plus a live status_url — or the completed ranking envelope.
Minimal feature changes associated with exiting the risk pattern, for entities in a prior ranking. Rate-capped per entity.
The pattern the engine found for a prior ranking: a combination of conditions (feature + direction + threshold) with prevalence and lift.
Lift, calibration coefficient, gate verdicts, and drift history for a prior ranking.
Context metrics and exposure/recourse figures attached to a prior ranking.
REST API
The same product surface over HTTP for clients that don’t speak MCP. OpenAPI 3.1 schema at /docs/openapi.json.
POST https://hunter-seeker.net/api/v1/scores\n\n{ "outcome_column": "churned",\n "entity_column": "account_id",\n "horizon": "90d",\n "page": { "k": 20 } }Model quality
Every ranking carries its own quality block: top-decile lift on out-of-time holdout, the calibration coefficient refit that cycle, the gate verdicts with their thresholds, and drift history for the series. Call hs_model_quality with a ranking_ref to re-read it without spending a run.
Governance export
One bundle per run: gate decisions with recorded reasons, leak-guard exclusions and why, model quality, drift history, the append-only action ledger, the data fingerprint with ordered run events, and a bundle sha256. Shaped for SR 26-2 model-risk documentation and EU AI Act review.
Honest-empty
Below a validated lift of 1.5 on out-of-time holdout, the engine returns a structured refusal rather than a weak ranking. The refusal names the best candidate, the bar it missed, and the failing gate. Refused runs are never billed.
{ "result": "none",\n "reasons": ["validated lift 1.31 < 1.5 surface bar"],\n "gate_verdicts": ["holdout gate: FAIL"],\n "provenance": { "engine_version": "0.2.2",\n "core_hash": "4d24e9fc…" } }Security & data
Raw data is processed for the run and then discarded; we retain derived facts and entity IDs only. Per-tenant isolation with row-level security, no bulk export beyond your own entities, and per-tenant rate caps on counterfactual access. We do not train on your data.