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mcp server

GammaRips Options Intelligence

Anti-firehose options-flow data for AI agents: curated daily pool, features, realized outcomes.

Description as published by the maintainer. Source

  • version 4.0.0
  • active

active — Most recent push to the repository was 2026-07-30.

What this server can do

9 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.

get_daily_report(date, view, limit)
The daily intelligence report. Two `view`s: * view="report" (DEFAULT) — the full report (title, markdown content, scan_date) for `date`, or the most recent report if `date` is omitted. * view="list" — 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 — how many reports (default 10, clamped 1-30).
get_liquidity(live, contract, contracts, scan_date)
FRESH (entry-day) liquidity — 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 — 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 — the WHOLE current pool (or your `contracts` shortlist, max 60) in ONE call — 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 — 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 — force a fresh upstream fetch.
get_market_calendar_status(view)
Market-calendar reference. Two `view`s: * view="status" (DEFAULT) — is the US equity market open today, plus the next open/close, holiday, and early-close flags (NYSE calendar, deterministic — no "is the market open?" hallucination). * view="scan_dates" — which recent scan dates have GammaRips data, with per-date signal counts (the pool's data-availability calendar). Args: view: "status" (default) | "scan_dates".
get_playbook(name, field)
Methodology + reference, versioned server-side (re-fetch rather than caching long-term). Arg-driven: * `field` given — 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 — 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 — 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`).
get_pool(view, limit, fields, offset, ticker, summary, direction, min_score, scan_date)
The GammaRips candidate pool for a scan date. One tool, four `view`s: * view="enriched" (DEFAULT) — the curated AI-enriched pool: news, technicals, catalyst, a delta-targeted recommended contract, and the 60-day momentum feature `mom_60`. Enrichment gate: overnight_score>=4 AND directional UOA>$500K, edge-ranked to the top ~50 BULLISH names. 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" — the wide pre-curation overnight scan (where unusual options activity concentrated across the whole universe, BEFORE curation). Honors `direction`, `min_score`, `ticker`, `limit`. * view="features" — 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" — 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 — 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 — 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 — True=compact columns, False=full rows. fields: enriched only — explicit strict column projection. offset: enriched only — pagination offset.
get_regime_context(scan_date)
Point-in-time market-regime context for a scan date: VIX close, VIX3M, SPY trend state, and the 5-day VIX delta — 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 — 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}
get_signal(full, view, ticker, contract, scan_date, expiration)
Deep dive on a single ticker/contract. Two `view`s: * view="detail" (DEFAULT) — 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" — 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 — 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 — YYYY-MM-DD (default: latest for the ticker). full: detail only — include the long narrative fields. expiration: earnings only — option expiration YYYY-MM-DD to test. contract: earnings only — OCC ticker supplying ticker+expiration.
query_outcomes(days, rule, view, limit, stops, ticker, horizon, outcome, targets, group_by, stop_pct, delta_max, delta_min, direction, scan_date, trail_pct, target_pct, exit_reason, include_open, scan_date_to, activation_pct, aggregate_only, policy_version, scan_date_from, min_premium_score, min_overnight_score)
The realized-outcome + receipts substrate behind the engine. One tool, nine `view`s. Whole-pool composites under any FIXED exit are NEGATIVE by construction — these are a research surface (how outcomes distribute across features and exits), never a strategy track record. * view="labels" (DEFAULT) — 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) — 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" — 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" — 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 — 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" — 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" — 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" — UNDERLYING-STOCK direction outcomes for the broad pool (NOT option PnL). Filters scan_date, ticker, direction, outcome. * view="win_rate" — aggregate UNDERLYING-direction win rate over `days` (NOT option PnL; headline key carries its universe). * view="positions" — 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" — 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 — 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 — summary stats instead of rows. On `surface` this is also the only mode immune to the 200-row cap. include_open: surface view — include not-yet-closed windows. targets / stops: harvest view — 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) — 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 — not merely older exit mechanics — 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.
replay_contract(date, to_date, contract, stop_pct, from_date, target_pct, granularity)
Raw option price data for YOUR OWN entry/exit rule. This server does NOT simulate or validate exits — it returns bars (the RM-002/RM-004 boundary). Two `granularity` modes: * granularity="minute" (DEFAULT) — 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" — 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 — 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 — ET session date YYYY-MM-DD (required). granularity: "minute" (default) | "day". target_pct: minute mode — optional +X% level for first-crossing. stop_pct: minute mode — optional -Y% level for first-crossing. from_date: day mode — start YYYY-MM-DD (default: 30d before to_date). to_date: day mode — end YYYY-MM-DD inclusive (default: today ET). Required: contract.

Last successful function declaration observed on . Source: https://mcp.gammarips.com/mcp. We list what the server declared; we do not call any of these functions.

Endpoint status observed on . Source: https://mcp.gammarips.com/mcp.

Signals

These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.

Signal Value What it measures Window Observed Source
GitHub stars 0 Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. cumulative, all time GitHub
Last commit 2026-07-30 Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. point in time GitHub
Open issues 1 Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. as of fetch GitHub
Latest published version 4.0.0 Latest version string the maintainer published to the registry. as of fetch Model Context Protocol
Registry record last updated 2026-07-18 When the registry record was last updated by its maintainer. point in time Model Context Protocol
License MIT Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. as of fetch GitHub
First listed in the MCP Registry 2026-07-18 Date this server was first published to the official MCP Registry. Not a usage or quality measure. point in time Model Context Protocol
repository status active The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. as of fetch GitHub
mcp tools declared 9 tools Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. as of probe mcp.gammarips.com
mcp endpoint status ok The server listed 9 functions when asked. as of probe mcp.gammarips.com

Where to get it

This record as data

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Sources

  1. DevDizzle/gammarips-mcp on GitHub — GitHub, observed , trust tier 3.
  2. Tools declared by the MCP server at https://mcp.gammarips.com/mcp — mcp.gammarips.com, observed , trust tier 4.
  3. Official MCP Registry — Model Context Protocol, observed , trust tier 1.