"Tide" matching MCP tools:

• polymarket_fill_riskA

  Noaa TidesB

  Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).

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• noaa_get_water_levelsA

  NOAA Tides and CurrentsA

  Get observed water levels from a NOAA tide station as a time series. Choose the interval: "6" = standard 6-minute observations (preliminary or verified, max 31 days per request), "1" = 1-minute preliminary data (max 4 days), "hourly" = verified hourly heights (max 1 year). Heights are relative to the requested datum (MLLW by default — the US nautical chart zero). Returns per record: t (timestamp in requested time zone), v (height), s (sigma), f (quality flags, decoded in output), q (p=preliminary, v=verified). Recent data is preliminary; verification takes days to weeks. Use for: "what is the water level right now" (date=latest), storm surge analysis, comparing observed vs predicted tide. Do NOT use for future tides — use noaa_get_tide_predictions.

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• noaa_search_stationsA

  NOAA Tides and CurrentsA

  Search the NOAA CO-OPS station directory by capability type, name, and/or state. Filter with: - type: what the station does (waterlevels, tidepredictions, currents, currentpredictions, met, ...) — pick the type matching the data you plan to request. - name: case-insensitive substring ("San Francisco", "Boston"). - state: two-letter code ("CA", "MA"). Returns id, name, location, tide type, Great Lakes flag, and for prediction stations whether they are reference (R, harmonic) or subordinate (S, offset-based — hilo predictions only). Results are paginated (limit/offset). For proximity search by coordinates use noaa_find_nearest_stations instead.

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• crypto_pricesA

  chainpulse — real-time crypto + prediction market data for AI agentsA

  Real-time USD spot prices for crypto assets. Accepts major symbols (BTC, ETH, SOL, USDC, USDT, DAI, BNB, XRP, ...), any CoinGecko id as "coingecko:<id>", or any token by "<chain>:<tokenAddress>". Aggregated feed with per-coin confidence score, ~15s freshness. Paid tool: $0.001 per call via x402 (USDC on Base).

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• weather.forecastA

  Abstraxn Agent LayerA

  Weather data from a global weather data provider — current conditions, short-range forecast, astronomy, historical, marine, and location search. Free, read-only, no wallet needed. Every action requires `q`, a location: a city name (e.g. "Paris"), "lat,lon" (e.g. "48.85,2.35"), a US/UK/Canadian postal code, or an IATA airport code. Pick one `action`: - current: current conditions for `q`. Optional `aqi` (default false) adds basic air quality data. - forecast: forecast for `q`. Optional `days` — this deployment runs on a data plan capped at 3 days, so only 1-3 is accepted; omit for the provider default. Optional `aqi`, `alerts` (default false, adds active weather alerts for the location where available). - astronomy: sunrise/sunset/moonrise/moonset/moon phase for `q` on `date` (required, YYYY-MM-DD). - search: resolve a fuzzy `q` into matching locations (name, region, country, lat/lon) — use this first if you only have an approximate place name and need to disambiguate. - history: past weather for `q` on `date` (required, YYYY-MM-DD, must be yesterday). This deployment enforces a free-tier data plan that only allows yesterday's date — any other date is rejected before a provider call is made. - marine: marine/sailing conditions for `q`. This deployment runs on a data plan limited to 1 day of data with no tide information. Results are for general informational purposes only — do not use them as the sole basis for decisions involving personal safety, aviation, marine navigation, or emergency planning.

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• weather.forecastA

  AbstraxnA

  Weather data from a global weather data provider — current conditions, short-range forecast, astronomy, historical, marine, and location search. Free, read-only, no wallet needed. Every action requires `q`, a location: a city name (e.g. "Paris"), "lat,lon" (e.g. "48.85,2.35"), a US/UK/Canadian postal code, or an IATA airport code. Pick one `action`: - current: current conditions for `q`. Optional `aqi` (default false) adds basic air quality data. - forecast: forecast for `q`. Optional `days` — this deployment runs on a data plan capped at 3 days, so only 1-3 is accepted; omit for the provider default. Optional `aqi`, `alerts` (default false, adds active weather alerts for the location where available). - astronomy: sunrise/sunset/moonrise/moonset/moon phase for `q` on `date` (required, YYYY-MM-DD). - search: resolve a fuzzy `q` into matching locations (name, region, country, lat/lon) — use this first if you only have an approximate place name and need to disambiguate. - history: past weather for `q` on `date` (required, YYYY-MM-DD, must be yesterday). This deployment enforces a free-tier data plan that only allows yesterday's date — any other date is rejected before a provider call is made. - marine: marine/sailing conditions for `q`. This deployment runs on a data plan limited to 1 day of data with no tide information. Results are for general informational purposes only — do not use them as the sole basis for decisions involving personal safety, aviation, marine navigation, or emergency planning.

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• request_api_keyA

  Nefesh — Real-Time Human State Awareness for AIA

  Request a free Nefesh API key. No existing API key needed for this call. IMPORTANT: You MUST ask the user for their real email address before calling this tool. Do NOT invent, guess, or generate an email address. The user will receive a verification link they must click to activate the key. Without clicking that link, no API key will be issued. Disposable or temporary email services are blocked. Example prompt to the user: "What is your email address? You will receive a verification link to activate your free API key." Flow: call this with the user's real email, then poll check_api_key_status every 10 seconds until status is 'ready'. Free tier: 1,000 calls/month, all signal types, 10 req/min. No credit card.

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• nausika_tidesA

  NausikaA

  Tide predictions or station discovery at a coordinate (latitude, longitude). Default: predictions from the nearest NOAA station; outside US waters falls back to a global modeled-tide source (forecast horizon ~15 days — longer windows are truncated, not rejected). Set stations_only=true to discover stations (capped by limit). Tune the window with begin_date (YYYYMMDD) + range_hours, the reference with datum, and output units (metric/english). The modeled path reports range_m (peak-to-trough). Across most of the Mediterranean this is under 0.3 m, i.e. negligible for recreational navigation — the response says so explicitly, and you should not present such values as an actionable tide window. Tides matter on the Atlantic coasts, in the Gulf of Gabès, the northern Adriatic, and in the tidal streams of the Messina and Gibraltar straits. Example: latitude=37.77, longitude=-122.42. Chain nausika_geocode for place→coordinates; pair with nausika_marine_forecast.

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• search_withinA

  Noaa TidesB

  Semantic search INSIDE a fetched record. Pass the text you already pulled (e.g. a SEC 10-K body, an article, a long tool result) plus a natural-language query; get back the top-N passages with character offsets and similarity scores. Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter, and every passage carries an offset so the agent can verify a verbatim quote. Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document. BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).

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• deep_researchA

  Noaa TidesB

  ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,798 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).

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• entity_profileA

  Noaa TidesB

  "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when `value` was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. `sources_used` / `sources_failed` say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit `notes` line, not a bare failure. `type` accepts "company" or "ticker" interchangeably — both take the same `value` shapes above.

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• recent_changesA

  Noaa TidesB

  "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

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• polymarket_arbitrageA

  Noaa TidesB

  Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.

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• noaa_marine_get_conditionsA

  noaa-marine-mcp-serverA

  Live marine conditions from an NDBC buoy: wave height/period/direction, wind speed/gust/direction, sea-surface temperature, air temperature, barometric pressure, and dew point. All values are SI units — wind in m/s, wave height in m, pressure in hPa, temperatures in °C. Exceptions: TIDE is in feet and VIS is in nautical miles (rarely populated at offshore buoys). Numeric fields are null when the buoy sensor did not report a value — this is normal for offshore buoys. Observations are updated approximately every 10 minutes; data may be 10–20 minutes old. Use noaa_marine_find_stations with source="ndbc" and types=["met"] to find station IDs near a location — met-flagged stations are the ones most likely to serve live conditions. Roughly a third of active NDBC stations report neither meteorological nor current data, and most of those have no observation file, so omitting the types filter will surface station IDs this tool cannot read.

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• noaa_get_water_level_summariesA

  NOAA Tides and CurrentsA

  Get verified summary water-level products from a NOAA station: - high_low: each day's observed highs/lows with ty = HH (higher high), H, L, LL (lower low). Max 1 year per request. - daily_mean: daily mean levels — GREAT LAKES STATIONS ONLY; NOAA requires local standard time, which this tool applies automatically. Max 10 years. - daily_max_min: daily maxima/minima from hourly and 6-minute data with completeness percentages. Max 10 years. - monthly_mean: monthly tidal datum means (columns MHHW, MHW, MSL, MTL, MLW, MLLW, DTL, GT, MN, DHQ, DLQ, HWI, LWI, highest, lowest). Max 200 years — ideal for long-term climatology. Use for: historical extremes, mixed-tide analysis (HH vs H), long-term averages. For raw time series use noaa_get_water_levels; for future tides use noaa_get_tide_predictions.

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• noaa_get_tide_predictionsA

  NOAA Tides and CurrentsA

  Get NOAA harmonic tide predictions (future or past) for a station. interval="hilo" (recommended for "when is high/low tide") returns the daily tide events with type H/L — up to 10 years per request. Other intervals (h, 1, 5, 6, 10, 15, 30, 60 minutes) return a height time series — up to 1 year per request. Heights are relative to the requested datum (MLLW default). Notes: - Great Lakes stations have NO tide predictions (lake levels are not tidal). - Subordinate stations (type "S") only support interval=hilo; use the station's reference (R) station for interval series. - Predictions are astronomical only — they exclude weather effects (storm surge, wind setup). Compare with noaa_get_water_levels for actual conditions.

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• noaa_get_station_infoA

  NOAA Tides and CurrentsA

  Get a NOAA station's full metadata record: location, state, time zone, tide type, Great Lakes flag, capability flags, and links to available sub-resources. Optionally expand sub-resources inline via the "expand" list: - details (established/removed dates), sensors (installed instruments + elevations), floodlevels (NOS/NWS minor/moderate/major flood thresholds), benchmarks, products (available data page links), notices, disclaimers — for water-level stations - bins (ADCP depth bins), deployments — for current stations (alphanumeric IDs) Use this before requesting data to confirm what the station actually collects. For datum values use noaa_get_station_datums; for harmonic constituents use noaa_get_harmonic_constituents.

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• noaa_get_harmonic_constituentsA

  NOAA Tides and CurrentsA

  Get the harmonic constituents NOAA uses to compute tide or current predictions at a station — the amplitude, phase, and angular speed of each tidal constituent (M2, S2, N2, K1, O1, ...). For water-level stations: amplitude (feet/meters), phase_GMT and phase_local (degrees), speed (degrees/hour). For current stations (alphanumeric IDs) constituents are current ellipses (major/minor amplitudes and phases per depth bin — pass bin to filter). Use for: building custom tide computations, checking a station's dominant constituents (M2 amplitude indicates semidiurnal range), verifying whether a station is harmonically predicted at all. Only reference (R) stations have constituents — subordinate stations use offsets (noaa_get_prediction_offsets).

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• tide_blast_radiusA

  RazielA

  Run a Blast Radius Assessment of an EXISTING app: an adversarial, vendor-neutral map of where authority is concentrated to a single point (whoever obtains that one thing obtains everything it governs), scored by blast radius (Total/Systemic/Contained/Limited) across three cores — Identity, Governance, Access — and delivered as a director-facing PDF. Phase 1 names no vendor; an opt-in Phase 2 companion explains how TideCloak shrinks each blast radius. Use this when the user wants to 'assess', 'red team', 'threat model', 'find the security gaps in', or make a before/after security case for an existing application.

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• sanger_knockin_quantA

  workbenchA

  Measure the rate of a SPECIFIC intended edit from a pair of Sanger traces — an unedited control and the edited pool — by decomposing the edited trace onto three things at once: the wild-type allele, the intended edited allele, and the unintended indels. Serves both readouts that need this: HDR knock-in rate (what fraction of the pool carries the donor's edit, including an insert of novel sequence), and prime editing (the pegRNA's intended substitution, insertion, deletion or replacement as the intended column, and the indel byproducts at the nick as the shift columns). This is what sanger_indel_spectrum cannot do: that tool's basis is indexed by indel LENGTH, so an intended 6 bp knock-in and an accidental 6 bp NHEJ deletion are one column there. Returns knock-in / wild-type / unintended-indel percentages, the byproduct spectrum by shift, and the R² that says whether the model fits your traces at all. Non-negative least squares, so no allele is ever assigned a negative share. For a substitution or replacement the reference allele you name is checked against the control read before anything is fitted; an insertion and a deletion name no reference bases, so there only the position can be range-checked. PREDICTED, NOT MEASURED. Every run reports its own R²: how much of the observed window the basis actually explains, measured on YOUR traces, where a low value means the model is wrong here rather than that the edit is weak. On agreement with a reference method for real samples — amplicon sequencing or clonal genotyping — none is published for this implementation. The underlying decomposition is TIDE/TIDER's, whose authors report their own concordance, and that number does not transfer to this code so it is not quoted. This implementation's near-exact recovery of synthetic mixtures is deliberately not offered as validation: a synthetic mixture is built from the same idealised one-hot peaks the basis assumes, so recovering it tests the arithmetic and cannot test the assumption. Valid for: A pool whose intended edit is known EXACTLY, read against a control amplicon of the same locus and chemistry, with both reads extending well past the edit. The novel inserted bases of a knock-in carry an assumed peak shape rather than a measured one (returned as constructedPositions) — the more of the window they occupy, the more of the fit is testing that assumption. NOT valid when the reported R² is low; nor for separating an intended pure DELETION from an unintended indel of the same net length ANYWHERE in the window, not only one at the same site (the tool reports which case it is in `sameShiftByproduct`: when that column is not fitted, knockinPercent is the sum of the two); nor for telling an on-target knock-in from a random integration of the same donor; nor for resolving haplotypes, since a Sanger trace of a pool has no phase information.

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• bcb_indicadores_atuaisA

  Banco Central do Brasil (BCB) — SGS Time Series MCP ServerA

  Atalho que retorna, em uma única chamada, o valor mais recente dos principais indicadores da economia brasileira: Selic (meta do Copom), IPCA mensal, IPCA acumulado 12 meses, dólar comercial de venda (série diária) e IBC-Br. Não recebe parâmetros. Quando usar: para um panorama econômico rápido. Quando NÃO usar: para qualquer outra série, para dados históricos ou para escolher o período use bcb_serie_ultimos ou bcb_serie_valores. Retorna: `consultadoEm` (timestamp ISO 8601) e `indicadores` (array com indicador, codigo, data, valor — ou `erro` no item). Resiliente: cada indicador é buscado de forma independente, então a falha de um não derruba os demais. Comportamento: consome a API pública SGS do Banco Central do Brasil — sem autenticação, chave de API ou cadastro, e sem limite de requisições divulgado (uso é best-effort). Em falha transitória ou timeout a chamada é repetida automaticamente (até 3 tentativas, backoff exponencial); persistindo o erro, retorna `isError: true` com mensagem em português (HTTP 404 = série inexistente ou sem dados no período solicitado). O resultado vem como JSON tanto em texto quanto em `structuredContent` (conforme o outputSchema); datas no formato dd/MM/yyyy e valores numéricos (ponto decimal).

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