此 MCP 可以做什么
Provides curated options-flow candidate pools, contract liquidity, market-regime context, trading signals, realized outcomes, and historical contract price data.
功能
工具
9
工具
get_daily_report
Daily Report
The daily intelligence report. Two `view`s:
* view="report" (DEFAULT) â the full report (title, markdown content,
scan_date) for `date`, or the most recent report if `date` is omitted.
* view="list" â recent reports, most recent first (scan_date, title,
created_at), titles deduped. Use `limit`.
Args:
date: report date YYYY-MM-DD (report view; default: most recent).
view: "report" (default) | "list".
limit: list view â how many reports (default 10, clamped 1-30).
只读
幂等
输入模式
{'type': 'object', 'title': 'get_daily_reportArguments', 'properties': {'date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Date', 'default': None}, 'view': {'type': 'string', 'title': 'View', 'default': 'report'}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 10}}}
get_liquidity
Contract Liquidity
FRESH (entry-day) liquidity â the read the pool's session-frozen
`recommended_oi`/`recommended_volume` cannot give you (the overnight sweep
only becomes OI the next morning). Two modes, chosen by whether you pass a
single `contract`:
* `contract` given â ONE contract's snapshot: open interest, session
volume, last trade, day range, underlying price, greeks. Cache-first
(the engine re-reads the pool every ~10 min in market hours); pass
live=true to force a fresh upstream fetch or read a contract NOT in
today's pool.
* `contract` omitted â the WHOLE current pool (or your `contracts`
shortlist, max 60) in ONE call â the batch companion for the ~10:00 ET
decision window. Most-recent read per contract with explicit `as_of`.
Deliberately serves NO bid/ask/mid/spread (not available on the current
data plan â absent, not NULL). Judge fill risk from open_interest (updates
once each morning), day_volume (live session), last_trade recency, and the
day range.
Args:
contract: OCC ticker for the single-contract mode (verbatim from the
pool's `recommended_contract`). Omit for the whole-pool batch.
scan_date: pool date YYYY-MM-DD (batch mode; default: latest pool).
contracts: optional shortlist filter for the batch mode (max 60).
live: single-contract mode â force a fresh upstream fetch.
只读
幂等
输入模式
{'type': 'object', 'title': 'get_liquidityArguments', 'properties': {'live': {'type': 'boolean', 'title': 'Live', 'default': False}, 'contract': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Contract', 'default': None}, 'contracts': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Contracts', 'default': None}, 'scan_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Scan Date', 'default': None}}}
输出模式
{'type': 'object', 'title': 'get_liquidityDictOutput', 'additionalProperties': True}
get_market_calendar_status
Market Calendar Status
Market-calendar reference. Three `view`s:
* view="status" (DEFAULT) â is the US equity market open today, plus the
next open/close, holiday, and early-close flags (NYSE calendar,
deterministic â no "is the market open?" hallucination).
* view="scan_dates" â which recent scan dates have GammaRips data, with
per-date signal counts (the raw scan's data-availability calendar).
* view="freshness" â is the pool you are about to trade the right pool?
Returns schema "pool-freshness/1": expected_scan_date (the last NYSE
session before today), each pipeline stage (scan, enrichment,
liquidity) with its latest date, row count for the expected date,
and ok (true / false = overdue / null = could not check); the
enrichment stage also gives expected_rows (the rows the enrichment
filter must produce, so rows < expected_rows is a partial pool); the
scan_date get_pool(view="enriched") serves by default
(pool_scan_date) and its row count (pool_rows), `fresh`, and machine
`reasons` (scan-stale, enrichment-stale, liquidity-stale, pool-stale,
pool-empty, unknown-<stage|pool>). Fail-closed: an unknown is never
fresh. A stage not yet due reports ok=true, due=false; before the
06:00 ET enrichment, fresh is false with reason pool-stale because
the next pool does not exist yet. No row floor is applied; apply
your own to pool_rows. Cached up to 60 s.
Args:
view: "status" (default) | "scan_dates" | "freshness".
只读
幂等
输入模式
{'type': 'object', 'title': 'get_market_calendar_statusArguments', 'properties': {'view': {'type': 'string', 'title': 'View', 'default': 'status'}}}
get_playbook
Methodology Playbook
Methodology + reference, versioned server-side (re-fetch rather than
caching long-term). Arg-driven:
* `field` given â the plain-English DEFINITION + role of a signal field
(deterministic lookup, no LLM). e.g. field="mom_60". The response's
`available_fields` lists every documented field.
* `name` given â a methodology playbook (markdown) by name, OR two
special reference pages:
- name="schema" (or "data-contract") -> the machine-readable
substrate DATA CONTRACT: every outcome/label column with its
leakage classification (feature|label|opportunity|
regime_telemetry|identity) and as-of boundary. Only `feature`
columns are safe as selection inputs.
- any other name -> the playbook markdown (start-here,
daily-workflow, run-your-own-tournament, exit-lab,
leakage-and-data-contract, changelog).
* neither â the CATALOG of published playbooks (name/title/summary),
plus a pointer to the field dict (`field=`) and schema page.
Args:
name: playbook name, or "schema"/"data-contract" for the data contract.
field: a signal field name to explain (overrides `name`).
只读
幂等
输入模式
{'type': 'object', 'title': 'get_playbookArguments', 'properties': {'name': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Name', 'default': None}, 'field': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Field', 'default': None}}}
get_pool
Candidate Pool
The GammaRips candidate pool for a scan date. One tool, four `view`s:
* view="enriched" (DEFAULT) â the AI-enriched pool: news, technicals,
catalyst, the recommended contract (an OTM call chosen on contract
liquidity), and the 60-day momentum feature `mom_60`. Funnel for
scan_date >= 2026-08-24 (liquid-universe era): the 100 most liquid
optionable names, BULLISH only, one call each, roughly 40-50 rows.
Liquidity decides membership, not unusual activity; the $500K UOA
floor is retired and `overnight_score>=1` is a cosmetic floor.
Earlier scan dates come from the prior UOA-gated funnel (UOA>$500K,
top-50 BULLISH); the two eras are not one population.
This is the daily candidate set your agent reasons over to its OWN
contract (see get_playbook("run-your-own-tournament")). Served from a
leakage-safe view (forward-outcome columns physically stripped);
`summary=True` gives ~21 decision columns, `fields=[...]` a strict
projection, `summary=False` full rows, `offset` pages.
* view="raw" â the wide overnight scan BEFORE the pool cut (the ranked
liquid universe for scan_date >= 2026-08-24; the market-wide
unusual-activity scan for earlier dates). Honors `direction`,
`min_score`, `ticker`, `limit`.
* view="features" â point-in-time FEATURE VECTORS from the leakage-safe
allowlist view `enriched_features_v1` (identity + features + cohort
metadata only; no outcome/label/telemetry column can appear). The
quantitative substrate for joining against query_outcomes. Lags the
live pool by ~1-2 trading days.
* view="preview" â a minimal public teaser (ticker, direction, score,
headline, directional UOA) for the most recent scan; no contract
specifics or thesis.
TIER: view="preview" is FREE (no key). The enriched / raw / features views
are the paid product â they require an active pro subscription key; an anon
call to them returns `subscription_required` (get_pool(view='preview') is
named as the free entry point).
Liquidity caveat (all views): `recommended_oi`/`recommended_volume` are
scan-time snapshots, not live values; `recommended_spread_pct` is
permanently NULL on the current data plan â re-check with get_liquidity.
Args:
view: "enriched" (default) | "raw" | "features" | "preview".
scan_date: YYYY-MM-DD (default: latest available scan for the view).
direction: "bull"/"bear" prefix filter (enriched / raw).
ticker: exact ticker filter (enriched / raw / features).
min_score: overnight_score floor (raw view only; clamped 0-10).
limit: max rows (enriched/raw clamp 1-50, features 1-100, preview 1-20).
summary: enriched only â True=compact columns, False=full rows.
fields: enriched only â explicit strict column projection.
offset: enriched only â pagination offset.
只读
幂等
输入模式
{'type': 'object', 'title': 'get_poolArguments', 'properties': {'view': {'type': 'string', 'title': 'View', 'default': 'enriched'}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 25}, 'fields': {'anyOf': [{'type': 'array', 'items': {'type': 'string'}}, {'type': 'null'}], 'title': 'Fields', 'default': None}, 'offset': {'type': 'integer', 'title': 'Offset', 'default': 0}, 'ticker': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Ticker', 'default': None}, 'summary': {'type': 'boolean', 'title': 'Summary', 'default': True}, 'direction': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Direction', 'default': None}, 'min_score': {'type': 'integer', 'title': 'Min Score', 'default': 0}, 'scan_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Scan Date', 'default': None}}}
get_regime_context
Market Regime Context
Point-in-time market-regime context for a scan date: VIX close, VIX3M,
SPY trend state, and the 5-day VIX delta â all as-of <= scan_date (the
selection point, leakage-safe), plus the engine's regime safety rail
evaluated on those values.
The rail: the engine fail-closes (no trade) when spot VIX > VIX3M
(backwardation â the market pricing imminent volatility is an adverse
regime for short-dated directional longs).
Served from the labeled substrate, which lags the live pool by ~1-2
trading days. Values are constant per scan_date.
Args:
scan_date: YYYY-MM-DD. Defaults to the latest scan date carrying
regime features.
Returns:
{scan_date, vix_at_scan, vix3m_at_enrich, spy_trend_at_scan,
vix_5d_delta_at_scan, regime_rail_pass, rail_definition}
只读
幂等
输入模式
{'type': 'object', 'title': 'get_regime_contextArguments', 'properties': {'scan_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Scan Date', 'default': None}}}
输出模式
{'type': 'object', 'title': 'get_regime_contextDictOutput', 'additionalProperties': True}
get_signal
Signal Detail
Deep dive on a single ticker/contract. Two `view`s:
* view="detail" (DEFAULT) â the full enriched signal for one ticker:
thesis, catalyst, the recommended contract, and point-in-time
features (leakage-safe view). `full=true` includes the long narrative
(news_summary, flow_intent_reasoning). If the ticker isn't in the
pool for the date, the error lists the dates on which it does appear.
* view="earnings" â the doctrine earnings-window check (RM-003): the
next scheduled earnings date and whether it lands ON OR BEFORE the
contract expiration (`earnings_in_window`). The engine applies this
rail only at its own pick time, NOT in the pool, so pool rows CAN
carry earnings-window names â check every candidate yourself. Pass
the pool's `recommended_contract` and both ticker and expiration are
derived. FAIL-CLOSED: unknown date -> earnings_in_window=null, treat
as in-window.
Args:
ticker: underlying symbol (required for detail; optional for earnings
if `contract` is given).
view: "detail" (default) | "earnings".
scan_date: detail only â YYYY-MM-DD (default: latest for the ticker).
full: detail only â include the long narrative fields.
expiration: earnings only â option expiration YYYY-MM-DD to test.
contract: earnings only â OCC ticker supplying ticker+expiration.
只读
幂等
输入模式
{'type': 'object', 'title': 'get_signalArguments', 'properties': {'full': {'type': 'boolean', 'title': 'Full', 'default': False}, 'view': {'type': 'string', 'title': 'View', 'default': 'detail'}, 'ticker': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Ticker', 'default': None}, 'contract': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Contract', 'default': None}, 'scan_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Scan Date', 'default': None}, 'expiration': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Expiration', 'default': None}}}
输出模式
{'type': 'object', 'title': 'get_signalDictOutput', 'additionalProperties': True}
query_outcomes
Realized Outcomes
The realized-outcome + receipts substrate behind the engine. One tool,
nine `view`s. Whole-pool composites under any FIXED exit are NEGATIVE by
construction â these are a research surface (how outcomes distribute
across features and exits), never a strategy track record.
* view="labels" (DEFAULT) â row-level realized bracket LABELS joined to
point-in-time features. horizon "same_day" (live V7.1 GIGO +40/-30) or
"3d" (legacy +80/-60) â never pooled. NULL-label and illiquid rows
excluded (counts in meta). `aggregate_only=True` returns summary stats
instead of rows. Filters: scan_date_from/to, ticker, delta_min/max,
min_overnight_score, exit_reason.
* view="summary" â grouped aggregates over the labeled pool. `group_by`
one of none|delta_bucket|overnight_score|premium_score|exit_reason|
day_of_week|moneyness_bucket.
* view="surface" â the OPPORTUNITY SURFACE: per-contract realized MFE/MAE
excursions with NO exit applied (profit potential, exit free). Uses
scan_date OR a `days` lookback, `ticker`, `delta_min/max`,
`include_open`. `aggregate_only=True` returns MFE/MAE quantiles over
the FULL filtered set â use it for exit design. The row mode is capped
at 200 and truncates oldest-first WITHIN a scan_date, so its oldest
date is a highest-MFE-only slice; it reports `truncated`,
`matched_rows`, and `partial_scan_date` so you can see that happen.
* view="harvest" â the touch-probability curve: P(premium touched +X%)
with CIs, day-of-peak buckets, stop-touch rates. `targets`, `stops`,
date range, delta band.
* view="exit_rule" â RESEARCH-ONLY "bring your exit, we score it":
rule="bracket" (target_pct/stop_pct) or rule="trailing" (trail_pct,
activation_pct) scored against the surface / minute tape.
* view="signal_performance" â UNDERLYING-STOCK direction outcomes for
the broad pool (NOT option PnL). Filters scan_date, ticker, direction,
outcome.
* view="win_rate" â aggregate UNDERLYING-direction win rate over `days`
(NOT option PnL; headline key carries its universe).
* view="positions" â the RECEIPTS: realized (closed) paper trades from
the engine's own daily pick, row-level, cohort-filtered
(`policy_version`, default live). Over `days`, `limit`.
* view="performance" â cohort AGGREGATE of the receipts over `days`
(win rate, avg/median/best/worst), `direction`, `min_premium_score`,
`policy_version`. When the cohort has no closed trades, every aggregate
is `null` and `total_trades` is 0 â NEVER 0.0. A `null` here means "not
measured yet", not "zero percent"; do not render it as a result.
All returns are FRACTIONS (0.40 = +40%). Realized data serves closed
windows only. Paper-traded research data; not investment advice.
Args:
view: which surface (see above). Default "labels".
horizon: "same_day" | "3d" (labels/summary/exit_rule). If omitted, the
native default per view is used: labels/summary => "same_day" (the
live GIGO policy), exit_rule => "3d" (its excursion window).
group_by: summary grouping dimension.
scan_date / scan_date_from / scan_date_to: date filters (per view).
ticker / direction / delta_min / delta_max / min_overnight_score /
exit_reason / outcome: row/aggregate filters (per view).
days: lookback window (surface/win_rate/positions/performance).
limit: max rows (labels 1-200, signal_performance 1-50, positions 1-200).
aggregate_only: labels/surface views â summary stats instead of rows.
On `surface` this is also the only mode immune to the 200-row cap.
include_open: surface view â include not-yet-closed windows.
targets / stops: harvest view â PERCENT grids.
target_pct / stop_pct / rule / trail_pct / activation_pct: exit_rule view.
policy_version: positions/performance cohort filter. The live default
is the PAIR (policy label + cohort start date) â the label alone
does not define the cohort, since disowned cohorts remain in the
ledger under the same label. Responses carry `cohort_start`; a zero
row_count under the live cohort means it has not accrued closed
trades yet, not that there is no track record, and the aggregates
come back `null` rather than 0.0. Pass "all" for every era, but
note that "all" returns cohorts the engine has REPUDIATED â not
merely older exit mechanics â so it is not a track record and must
not be aggregated into one. Read the response `note` before
quoting any number from it.
min_premium_score: performance view floor.
只读
幂等
输入模式
{'type': 'object', 'title': 'query_outcomesArguments', 'properties': {'days': {'type': 'integer', 'title': 'Days', 'default': 30}, 'rule': {'type': 'string', 'title': 'Rule', 'default': 'bracket'}, 'view': {'type': 'string', 'title': 'View', 'default': 'labels'}, 'limit': {'type': 'integer', 'title': 'Limit', 'default': 100}, 'stops': {'anyOf': [{'type': 'array', 'items': {'type': 'number'}}, {'type': 'null'}], 'title': 'Stops', 'default': None}, 'ticker': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Ticker', 'default': None}, 'horizon': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Horizon', 'default': None}, 'outcome': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Outcome', 'default': None}, 'targets': {'anyOf': [{'type': 'array', 'items': {'type': 'number'}}, {'type': 'null'}], 'title': 'Targets', 'default': None}, 'group_by': {'type': 'string', 'title': 'Group By', 'default': 'none'}, 'stop_pct': {'type': 'number', 'title': 'Stop Pct', 'default': 30}, 'delta_max': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Delta Max', 'default': None}, 'delta_min': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Delta Min', 'default': None}, 'direction': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Direction', 'default': None}, 'scan_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Scan Date', 'default': None}, 'trail_pct': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Trail Pct', 'default': None}, 'target_pct': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Target Pct', 'default': None}, 'exit_reason': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Exit Reason', 'default': None}, 'include_open': {'type': 'boolean', 'title': 'Include Open', 'default': False}, 'scan_date_to': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Scan Date To', 'default': None}, 'activation_pct': {'type': 'number', 'title': 'Activation Pct', 'default': 0}, 'aggregate_only': {'type': 'boolean', 'title': 'Aggregate Only', 'default': False}, 'policy_version': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Policy Version', 'default': 'V7_1_TILTED_GIGO'}, 'scan_date_from': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Scan Date From', 'default': None}, 'min_premium_score': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'title': 'Min Premium Score', 'default': None}, 'min_overnight_score': {'anyOf': [{'type': 'integer'}, {'type': 'null'}], 'title': 'Min Overnight Score', 'default': None}}}
输出模式
{'type': 'object', 'title': 'query_outcomesDictOutput', 'additionalProperties': True}
replay_contract
Contract Price Replay
Raw option price data for YOUR OWN entry/exit rule. This server does NOT
simulate or validate exits â it returns bars (the RM-002/RM-004 boundary).
Two `granularity` modes:
* granularity="minute" (DEFAULT) â the intraday minute path for one
session (`date` required). Optionally pass a bracket (target_pct/
stop_pct, PERCENT of the 10:00 ET anchor) and the response also reports
the exact FIRST-CROSSING sequence measured from the tape. Pool
excursion windows are served from the engine's minute-path table;
anything else falls back to an upstream minute fetch.
* granularity="day" â the DAILY mark series (OHLCV) over a date range,
to mark a live paper position day by day or replay a closed one. Uses
`from_date`/`to_date` (span capped at 120 days); `date` is ignored.
Option tape is THIN â minutes/days with no prints have no bar; treat
touch times as evidence, not tick-perfect truth. Paper-trade research
data; not investment advice.
Args:
contract: OCC option ticker (e.g. "O:UNIT260717C00030000").
date: minute mode â ET session date YYYY-MM-DD (required).
granularity: "minute" (default) | "day".
target_pct: minute mode â optional +X% level for first-crossing.
stop_pct: minute mode â optional -Y% level for first-crossing.
from_date: day mode â start YYYY-MM-DD (default: 30d before to_date).
to_date: day mode â end YYYY-MM-DD inclusive (default: today ET).
只读
幂等
输入模式
{'type': 'object', 'title': 'replay_contractArguments', 'required': ['contract'], 'properties': {'date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'Date', 'default': None}, 'to_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'To Date', 'default': None}, 'contract': {'type': 'string', 'title': 'Contract'}, 'stop_pct': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Stop Pct', 'default': None}, 'from_date': {'anyOf': [{'type': 'string'}, {'type': 'null'}], 'title': 'From Date', 'default': None}, 'target_pct': {'anyOf': [{'type': 'number'}, {'type': 'null'}], 'title': 'Target Pct', 'default': None}, 'granularity': {'type': 'string', 'title': 'Granularity', 'default': 'minute'}}}
输出模式
{'type': 'object', 'title': 'replay_contractDictOutput', 'additionalProperties': True}
历史
近期工具变更
已更改
get_market_calendar_status
2026年10月1日 02:45
已添加
get_daily_report
2026年9月17日 12:41
已添加
get_playbook
2026年9月17日 12:41
已添加
get_market_calendar_status
2026年9月17日 12:41
已添加
get_regime_context
2026年9月17日 12:41
已添加
replay_contract
2026年9月17日 12:41
已添加
query_outcomes
2026年9月17日 12:41
已添加
get_liquidity
2026年9月17日 12:41
已添加
get_signal
2026年9月17日 12:41
已添加
get_pool
2026年9月17日 12:41
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