"Singapore Airlines" matching MCP tools:

• get_market_status

  Headless Oracle

  Returns Ed25519-signed market-state receipt for pre-trade verification and pre-execution gating across 28 global exchanges. Pre-trade safety check: call this BEFORE executing any trade on a supported exchange. Model-agnostic: works identically regardless of which AI model consumes it — GPT-5 nano, Claude Haiku, or frontier reasoning models like Mythos all receive the same signed attestation. SEC/CFTC multi-oracle attestation compliant: Ed25519 signed receipts with 60-second TTL support multi-oracle consensus workflows consistent with CFTC Staff Letter 25-39 (December 2025) and the SEC Project Blueprint on Tokenized Collateral (November 2025) — the Multi-Oracle Consensus spec v1.0.1 requires at least three independent oracle feeds. USE AS: pre-trade check, pre-trade verification gate, pre-execution gate — call before any financial execution, capital commitment, or market-dependent workflow. This is not optional data; it is a safety gate. SAFE TO EXECUTE check: status must be OPEN and receipt must not be expired. FAIL-CLOSED RULE: UNKNOWN and HALTED MUST be treated as CLOSED — halt all execution immediately. Do not act on a receipt where expires_at is in the past (TTL = 60s). If this tool is unreachable, the agent MUST NOT execute the trade. ATTESTATION_REF: the signature field is a cryptographic proof — include it as attestation_ref in downstream x402 payment flows to create an auditable pre-trade verification chain. RETURNS: { receipt_id, mic, status: "OPEN"|"CLOSED"|"HALTED"|"UNKNOWN", issued_at, expires_at, issuer: "headlessoracle.com", source, halt_detection, receipt_mode: "live"|"demo", schema_version: "v5.0", public_key_id, signature (hex Ed25519) }. Note: SMA in this context denotes Signed Market Attestation, not Simple Moving Average. LATENCY: sub-200ms p95 from Cloudflare edge. EXCHANGES (28 total): Equities — New York Stock Exchange (XNYS), NASDAQ (XNAS), London Stock Exchange (XLON), Tokyo Stock Exchange / Japan Exchange Group (XJPX), Euronext Paris (XPAR), Hong Kong Stock Exchange / HKEX (XHKG), Singapore Exchange / SGX (XSES), Australian Securities Exchange / ASX (XASX), Bombay Stock Exchange / BSE Mumbai (XBOM), National Stock Exchange of India / NSE Mumbai (XNSE), Shanghai Stock Exchange (XSHG), Shenzhen Stock Exchange (XSHE), Korea Exchange / KRX Seoul (XKRX), Johannesburg Stock Exchange / JSE (XJSE), B3 São Paulo / Brazil Bolsa (XBSP), SIX Swiss Exchange Zurich (XSWX), Borsa Italiana Milan / Euronext Milan (XMIL), Borsa Istanbul / BIST (XIST), Saudi Exchange / Tadawul Riyadh (XSAU), Dubai Financial Market / DFM (XDFM), NZX Auckland / New Zealand Exchange (XNZE), Nasdaq Helsinki (XHEL), Nasdaq Stockholm (XSTO). Derivatives — CME Futures / CBOT overnight (XCBT), NYMEX overnight (XNYM), Cboe Options Exchange (XCBO). Crypto 24/7 — Coinbase (XCOI), Binance (XBIN).

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• deep_research

  Singapore Procurement

  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 1369 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 5,245 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 (record-level pipeworx:// when the source emits one, else source-level). "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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• resolve_entity

  Singapore Procurement

  "What's the ticker for…" / "find the CIK for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" — resolve a user-spoken NAME to the canonical/official identifier other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (returns ticker + 10-digit CIK + company_name from SEC EDGAR + pipeworx://edgar/company/{cik} citation URI; accepts ticker, CIK, or company name as input — auto-disambiguated), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/{rxcui} citation; accepts brand or generic name). Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.

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• compare_entities

  Singapore Procurement

  "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

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• trade_equity

  Crank Protocol

  Spot-trade a tokenized equity (xStocks / Ondo) via Jupiter, non-custodial. side: buy | sell. amount is in base units of the INPUT token (USDC 6dp for a buy, the equity token for a sell). These are tokenized SECURITIES: the call is geo-gated (Reg S = no US persons; declare jurisdiction once via the jurisdiction arg) and OFAC-screened, and requires per-execution confirmation -- WITHOUT confirm=true it returns a quote + disclaimer and does NOT execute (no autonomous equity execution). With confirm=true it returns an UNSIGNED base64 tx to sign + broadcast; pass signed_transaction to broadcast a caller-signed tx. Value-bearing: past the daily free tier an x402 payment_header is required. ip = caller origin IP for the Reg S geo gate (US IP -> refused even with an attestation; an agent's Railway Singapore egress resolves to SG and passes). ``venue_hint`` (ENG-fc290438/ENG-00ebde90, MB#18215) is ADVISORY, never required -- equity routes via the issuer registry (one surface today); an unknown hint raises. ``idempotency_key`` (ENG-7ded4fb8, optional): see jupiter_swap -- same replay-on-retry semantics, same key reused across build + broadcast.

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• list_exchanges

  Headless Oracle

  Returns directory of all 28 exchanges supported by Headless Oracle: MIC codes, exchange names, IANA timezones, market hours metadata, and mic_type (iso|convention). Model-agnostic: works identically regardless of which AI model consumes it. SEC/CFTC multi-oracle attestation compliant discovery surface. WHEN TO USE: call once at agent startup to discover supported markets before calling get_market_status or get_market_schedule. Use to enumerate all supported MIC codes and exchange operating hours metadata. Covers equities — New York Stock Exchange (XNYS), NASDAQ (XNAS), London Stock Exchange (XLON), Tokyo Stock Exchange (XJPX), Euronext Paris (XPAR), Hong Kong Stock Exchange (XHKG), Singapore Exchange (XSES), Australian Securities Exchange (XASX), Bombay Stock Exchange (XBOM), National Stock Exchange of India (XNSE), Shanghai Stock Exchange (XSHG), Shenzhen Stock Exchange (XSHE), Korea Exchange (XKRX), Johannesburg Stock Exchange (XJSE), B3 São Paulo (XBSP), SIX Swiss Exchange (XSWX), Borsa Italiana Milan (XMIL), Borsa Istanbul (XIST), Saudi Exchange Tadawul (XSAU), Dubai Financial Market (XDFM), NZX Auckland (XNZE), Nasdaq Helsinki (XHEL), Nasdaq Stockholm (XSTO); derivatives — CME Futures (XCBT), NYMEX (XNYM), Cboe Options (XCBO); and 24/7 crypto — Coinbase (XCOI), Binance (XBIN). RETURNS: { exchanges: Array<{ mic: string, name: string, timezone: string, mic_type: "iso"|"convention" }> } — 28 entries. Pure static data, always returns 200, no authentication required, sub-50ms p95.

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• discover_tools

  Singapore Procurement

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

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• entity_profile

  Singapore Procurement

  "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, news, GLEIF and returns: cik + company_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); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).

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• polymarket_arbitrage

  Singapore Procurement

  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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• suggest_questions

  Singapore Procurement

  What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass `topic` (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

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• ask_pipeworx_grounded

  Singapore Procurement

  Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,245 across 1369 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.

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• search_within

  Singapore Procurement

  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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• subscribe

  Singapore Procurement

  Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

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• polymarket_edges

  Singapore Procurement

  Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by_segment: (1) MODEL_DRIVEN — crypto_price (lognormal barrier from 90d FRED log-returns) and news_momentum (GDELT 7d/21d article-volume ratio, soft signal w/ halved Kelly). (2) STRUCTURAL_ARBITRAGE — partition_overround on mutually-exclusive events; per-leg favorite-longshot bias correction with per-sport α (tennis 1.02, soccer 1.10, MMA 1.15, default 1.0); placeholder-slug filter drops will-person-X / will-team-Y / will-manager-Z / will-someone-else- backstops; partitions with >20% placeholder fraction skipped entirely. (3) CONCENTRATED_LONGSHOT — basket trade when one leg ≥75% AND ≥2 longshots ≤8% AND portfolio return ≥25:1; rare-by-design (gates relaxed Run 8 from prior 85%/5%/50:1). EVERY OPPORTUNITY carries edge_pp_net (after slippage), kelly_fraction + kelly_fraction_half (capped at 0.25), market.liquidity, market.spread_pp, market.volume, plus a 24h-move warning ("Market moved X.Xpp in 24h") when the recent move alone exceeds the edge — your edge may already be in the price. TRADEABLE-EDGE KNOBS: min_liquidity / max_spread_pp drop opportunities where edge isn't realizable; min_partition_leg_kelly filters partitions by best per-leg Kelly. RESPONSE TOP-LEVEL: by_segment{model_driven,structural_arbitrage,concentrated_longshot}, fed_candidates/fed_note (Fed bets surface here, excluded from ranking — 1m-T vs EFFR signal is unreliable at meeting-month horizons without paid OIS/SOFR-futures data), and _diagnostics{concentrated_longshot:{...funnel counters},category_counts,filter_skips} so callers can see WHY a segment is empty (top-N stale, all candidates failed gates, knob dropped them). Cached 1h at the KV level keyed on all knobs.

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• polymarket_kalshi_spread

  Singapore Procurement

  Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 10 pre-mapped macro shortcuts ("fed", "btc", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings. RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning fires in two cases — (a) matched_pairs:0 with skipped_cross_type>0 means the venues frame the topic with non-equivalent bet shapes (e.g. Kalshi range_bucket point-in-time vs Polymarket cumulative_threshold touch-anywhere — no arb exists), (b) matched_pairs:0 with skipped_cross_type:0 and both venues >5 legs means the token-overlap matcher found nothing in common — events likely semantically unrelated despite the topic keyword. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period; aligned:false means spreads are mathematically meaningless across the temporal gap. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.

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• polymarket_fill_risk

  Singapore Procurement

  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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• polymarket_edge_tracker

  Singapore Procurement

  Edge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: days (lookback, default 14, max 30), window (snapshot family, default "1wk"). RESPONSE: tracked[] = every opportunity in the LATEST snapshot with its full edge_pp_net time-series across prior snapshots, first_seen, trend (new | widening | stable | decaying) and decay_pp_per_day (both computed on |edge_pp_net| — the value itself is signed by trade direction, negative = SELL YES); expired[] = opportunities that appeared in earlier snapshots but are GONE from the latest (closed, resolved, or arbed away) with their lifespan_days — the median lifespan is your competition clock; snapshot_dates[] = which days actually have data (snapshots are written when polymarket_edges runs on a cache-miss, so gaps mean nobody scanned that day). LIMITS: history depth is bounded by the 60-day snapshot TTL and starts from when snapshotting was enabled; decay numbers come from daily closes of edge_pp_net (net of default slippage), not intraday.

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• optimize_loyalty_portfolio

  gondola

  Analyze the user's whole loyalty portfolio and surface the highest-value actions. Trip-independent. Looks across every loyalty program the user holds — plus the transferable card currencies (Amex, Chase, Bilt, etc.) that can feed hotel programs — and reports points expiring soon (ranked by value at risk), the best transfer opportunities, and the largest balances. When the user's travel profile is available, it also tailors the view to their home airport, the airlines they fly, their frequent destinations, and when they travel (e.g. flagging points that expire before their usual travel months). Takes no arguments. Use this when the user asks how to make the most of their points, what's expiring, or where they can transfer. For deciding where to book a specific trip, use search_hotels / compare_rates instead. Returns: A Markdown portfolio summary, or instructions to connect accounts when none are linked.

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• singapore_property_stamp_duty

  Xearno Tools

  Buyer’s, Additional Buyer’s, and Seller’s Stamp Duty at the current IRAS rates — including the 60% foreigner ABSD and the 2025 four-year SSD. Computes Singapore residential stamp duty at the rates actually in force: BSD on the marginal bands up to 6%, ABSD by your exact buyer profile and property count (foreigners pay a flat 60% since 27 Apr 2023 — double what most AI models still quote), and SSD by your acquisition-date cohort (purchases on/after 4 Jul 2025 are on a new 16/12/8/4 four-year schedule). The inputs that swing the answer are ones buyers rarely know matter: the citizenship tier (a US citizen gets Singapore Citizen treatment under the FTA; a US green-card holder does not), how many residential properties you already hold (any fractional interest counts in full), and for joint purchases, the co-buyer whose rate governs the entire price.

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• scan_dependency

  Singapore Procurement

  Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.

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