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754,981 tools. Updated 2026-11-07 07:59

"NFC" matching MCP tools:

  • Word-level diff of a North Carolina (NC) statute section between two versions. `mode="pending"` compares the text in force against an enacted-but-not-yet-effective variant — use this for "what will change on 1 October". `mode="observed"` compares versions this database has actually recorded, optionally between two dates. CANNOT show text from before the ingest's first observation: observed history begins then, so most sections have only one version and return diff: null. For earlier change dates use amendment_history; for pending text use pending_changes.
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  • 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}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. 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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  • 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}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. 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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  • 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}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. 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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  • 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}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. 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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  • 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}. FEES: every opportunities[] row and partition_check.arbitrage carry edge_pp_gross (== gap_pp / overround_pp), fees_pp, edge_pp_net, net_positive, plus polymarket_fee_pp, fee_basis and fee_categories[]. BOTH cost components are modeled: Polymarket's own per-category TAKER FEE (fee = shares × rate × p × (1-p), rates crypto 0.07 / sports-economics-culture-weather-other 0.05 / finance-politics-mentions-tech 0.04, geopolitics and world events fee-free; verified against Polymarket's own docs as of 2026-09-13) and Polygon gas (~$0.02/leg). The taker fee dominates: ~$1.75 per 100 shares on a crypto market at 50c versus $0.02 of gas, so rows that looked profitable before fleet #1927 may now show net_positive:false — that is the correction, not a regression. Each leg is priced at ITS OWN market's rate and price (the fee curve peaks at 50c and falls toward both extremes). fee_basis says where the rate came from: 'payload' (read off the market, the normal case), 'category' (mapped from its fee category), 'fee_free', or 'fallback' (rate unknown — charged at the modal 0.05 rather than assumed free, so an unreadable market is never reported as costless). Where fill_check reprices against live depth, this does NOT double-count that spread cost. 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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  • A
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    Provides read-only access to official SEFAZ BA NFC-e records through a single query tool, enabling users to consult fiscal documents from any MCP-compatible client. Operates as a hosted, prepaid service with pay-per-query pricing.
    MIT

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  • SEFAZ PB: NFC-e, official-source lookup. Platform-hosted, pay per query with prepaid credit.

  • SEFAZ MT: NFC-e, official-source lookup. Platform-hosted, pay per query with prepaid credit.

  • Create a signed Apple Wallet pass (.pkpass) and return a link to download it. Builds one pass in one of the five Wallet styles -- boardingPass, eventTicket, coupon, storeCard or generic -- from the text fields, colors, barcode and optional PNG images given below, signs it with this service's Apple Pass Type ID certificate, and returns an https download_url valid for 1 hour. Opening the link on an iPhone shows "Add to Apple Wallet". Passes install on any iOS version; the iOS 26/27 layouts fall back to the classic style on older iPhones. Barcodes: QR, PDF417, Aztec and Code128 on every iOS version; Code39, Codabar, EAN13 and ITF on iOS 27+. The barcode encodes exactly barcode_message. Gate and till scanners read that data, so a copy of an existing boarding pass, ticket or loyalty card only scans if barcode_message is the original barcode's content (airline boarding passes are usually PDF417 or Aztec, holding an IATA BCBP string such as "M1DOE/JANE ..."). This tool does not issue tickets, check anyone in, or contact airlines or venues. The link must be opened in Safari on the iPhone: Wallet adds a pass from Safari, but not from a .pkpass file handed over by another app. Google Wallet on Android also imports these files. Not supported: NFC passes. With updatable=True the pass can be changed later with update_wallet_pass, and copies already in Wallet refresh themselves. Its contents are then stored on this server for updatable_hours (1 hour by default, at most 30 days), then deleted. Returns {download_url, expires_in_seconds, serial_number, pass_type_identifier}, plus edit_token and updatable_until when updatable=True, and x402_setup (how to set up x402 payments, worth passing on to the user) when x402_ready=False. Pricing: a call is one create or one update. Free for 30 calls a day per caller IP (20 from 2026-11-18), while a shared pool of 500 free calls a day lasts; failed calls count too, and counts reset at 00:00 UTC. Past either limit, a call costs $0.01 in USDC on Base, paid with x402; the refusal carries the payment requirements, and a paid result includes the payment receipt. Payment is settled only after the pass is built, so a failed build is never charged. Args: style: one of "boardingPass", "eventTicket", "coupon", "generic", "storeCard". organization_name: shown as the pass issuer. description: accessibility description (required by Wallet, not usually shown). logo_text: text shown next to the logo image. transit_type: only for style="boardingPass" -- "Air", "Boat", "Bus", "Generic", or "Train" (default "Air"). barcode_message: raw text/data encoded into the barcode. Omit for no barcode. barcode_format: a format name or an ordered list of them; each becomes a barcode with the same message, and Wallet shows the first one the device supports. Nothing is added that you don't list. Formats: "QR" (default), "PDF417", "Aztec", "Code128" (all iOS versions), and iOS 27+ only: "Code39", "Codabar", "EAN13", "ITF" -- older iPhones skip these, so e.g. ["EAN13", "Code128"] shows EAN13 on iOS 27 and Code128 before it. EAN13 needs 12-13 digits, ITF an even number of digits, Code39 uppercase letters/digits. barcode_alt_text: human-readable text shown under the barcode (e.g. the card number). background_color / foreground_color / label_color: hex colors, e.g. "#1a1a19". relevant_date / expiration_date: ISO 8601 timestamps. locations: up to 10 places where the pass appears on the lock screen when the iPhone is nearby, each {"latitude": float, "longitude": float, "altitude": optional float, "relevantText": optional str shown on the lock screen, e.g. "Your gym card"}. Look up the coordinates of the actual branch, not just the brand. For boardingPass and eventTicket the pass is relevant near a location around relevant_date if one is set; the other styles use location alone. Wallet only shows a pass within its own default radius of a location, which is small for store cards and coupons. max_distance: meters; shrinks the default radius around every location (Wallet uses the smaller of the two, so it cannot enlarge it). Requires locations. voided: mark the pass voided/used (shows a "VOID" stamp). primary_fields / secondary_fields / auxiliary_fields / header_fields / back_fields: lists of {"key": optional str, "label": optional str, "value": str, "changeMessage": optional str} shown on the pass. changeMessage only matters on updatable passes: when an update changes that field's value, the iPhone shows it as a lock-screen notification, with %@ replaced by the new value (e.g. "You now have %@ points"); without %@ Wallet shows a generic message. Updates match fields by key, so give fields that will change an explicit key (auto keys are by position). serial_number: unique id for this pass; auto-generated if omitted. icon_color / icon_text: control the auto-generated icon (a colored square with initials) when icon_png_b64 is not supplied. logo_color: color of the auto-generated logo image, a wordmark of logo_text (or organization_name) drawn on a transparent background over background_color. Defaults to icon_color. Wallet also renders logo_text as text beside the logo image, so the generated wordmark repeats it -- set generate_logo=False to show only the text. icon_png_b64 / logo_png_b64: PNG to use instead of auto-generated art. Every *_png_b64 parameter takes either base64 PNG data or an https:// URL of an image (PNG, JPEG, WebP or GIF, up to 5 MB; non-PNG is converted to PNG). The URL is fetched once, when the pass is built. generate_logo: set False to include no auto-generated logo or primary logo at all (both are optional in Wallet; a supplied logo_png_b64/primary_logo_png_b64 is still used). poster: (iOS 27+) render as Apple's new full-bleed "Poster Generic" layout -- large background image, header field, up to 4 primary fields, up to 2 footer_fields, and a square QR code. Only for style "generic", "storeCard" or "coupon"; that style is kept as the fallback older iPhones display (secondary/auxiliary fields only show on the fallback). Good for memberships, loyalty cards and gift cards. footer_fields: up to 2 fields along the bottom of a poster pass (requires poster=True). background_png_b64: base64 PNG poster background, ideally 1035x1515 px (345x505pt @3x); a gradient in background_color is generated if omitted. Only used when poster=True. featured_actions: (iOS 27+) up to 2 tappable shortcut cards shown under the pass, each {"type": ..., "url": "https://..."}. type is one of: viewSchedule, watchTrailer, listenToMusic, call (url must be "tel:+..."), addToBalance, order, shop, membershipBenefits, bookAppointment, bookCar, bookFlight, bookStay, viewOffersRewards. Works on every style; ignored by older iPhones. semantics: machine-readable tags (Apple's SemanticTags) that Wallet uses for Siri/Maps/ Calendar suggestions on every style, and to lay out the semantic designs below. Values are emitted as given; unknown keys and wrong types are rejected. Dates are ISO 8601 with an offset. Common shapes: passengerName {"givenName", "familyName"}; flightNumber is a number (123, not "AI123"); seats [{"seatNumber", "seatRow", "seatSection", ...}]; venueLocation {"latitude", "longitude"}; totalPrice {"amount": "12.50", "currencyCode": "INR"}; eventType one of generic, livePerformance, movie, sports, conference, convention, workshop, socialGathering. semantic_layout: use Wallet's semantic design, with the classic style kept for older iPhones -- which only show primary/secondary/auxiliary fields, so still fill those. - boardingPass (iOS 26+, airline only, transit_type "Air"): live flight status, gate changes, badges. Requires semantics airlineCode, flightNumber, departureAirportCode, departureCityName, destinationAirportCode, destinationCityName, originalBoardingDate, originalDepartureDate, originalArrivalDate, passengerName, plus departure and destination time zones (IANA, e.g. "Asia/Kolkata"). Apple's docs call these departureLocationTimeZone/destinationLocationTimeZone but Apple's pass-builder code uses departureAirportTimeZone/destinationAirportTimeZone; either is accepted, and giving both is safest. - eventTicket (iOS 26+ "poster event ticket"): requires eventName, venueName, venueRegionName, venueRoom; sports also needs awayTeamAbbreviation and homeTeamAbbreviation, livePerformance needs performerNames. Apple says this design is meant for NFC entry, not barcodes, and NFC passes need an Apple entitlement this server doesn't have -- Wallet may show the classic event ticket instead. info_links: top-level links that fill the event guide (event tickets) or the airline and services page (boarding passes). URL keys (http/https): accessibilityURL, addOnURL, bagPolicyURL, merchandiseURL, orderFoodURL, parkingInformationURL, purchaseParkingURL, sellURL, transferURL, transitInformationURL, contactVenueWebsite, directionsInformationURL, changeSeatURL, entertainmentURL, purchaseAdditionalBaggageURL, purchaseLoungeAccessURL, purchaseWifiURL, upgradeURL, managementURL, registerServiceAnimalURL, reportLostBagURL, requestWheelchairURL, transitProviderWebsiteURL. Text keys: contactVenueEmail, contactVenuePhoneNumber, transitProviderEmail, transitProviderPhoneNumber. Extra images (base64 PNG or https URL). Which image shows where depends on style and iOS version (from Apple's Pass Designer docs); Wallet ignores an image a layout has no slot for: primary_logo_png_b64: max 126x30pt. Boarding pass and coupon on iOS 27+, event ticket on iOS 18+, poster. On those, the plain logo is only shown by older iOS. A wordmark is auto-generated for poster and semantic_layout passes unless generate_logo=False. secondary_logo_png_b64: max 135x12pt. Event tickets, iOS 18+. strip_png_b64: 375x144pt banner behind the primary fields. Coupon, store card and event ticket; not shown on iOS 26+ coupon/store card. thumbnail_png_b64: 90x90pt. Generic and event ticket. artwork_png_b64: 358x448pt poster event ticket artwork (eventTicket with semantic_layout, iOS 27+); if neither this nor background_png_b64 is given, a gradient in background_color is generated, since Wallet needs one of them. background_png_b64 is also used on eventTicket (blurred behind the classic ticket). updatable: keep this pass on the server so update_wallet_pass can change it later. The response then includes an edit_token: the only way to update the pass, and it can't be recovered, so give it to the user. Wallet registers each iPhone that adds the pass, and an update reaches them within seconds. The pass contents are stored (other passes only log the style and organization_name). Use for passes that change: loyalty points, gate or seat changes, memberships that can be cancelled. updatable_hours: how long an updatable pass can be updated, 1 (default) to 720 (30 days), counted from creation; updates don't extend it. Afterwards the stored pass is deleted and can't be changed again, while copies in Wallet stay as they last were. Pick it to cover the pass's useful life, e.g. until a flight lands or an event ends. Only with updatable=True. contact_email: required. The user's address, so the operator of this service can reach them about it, for example if it changes or breaks for them. Ask the user for it; never take it from the pass details or make one up. It isn't added to the pass, and it's kept in the request log. x402_ready: required. True if this client can pay with x402, False if it can't, "unknown" if you don't know. It shows the operator how many clients could pay past the free limit. Only logged: it changes neither price nor limits.
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  • Create a signed Apple Wallet pass (.pkpass) and return a link to download it. Builds one pass in one of the five Wallet styles -- boardingPass, eventTicket, coupon, storeCard or generic -- from the text fields, colors, barcode and optional PNG images given below, signs it with this service's Apple Pass Type ID certificate, and returns an https download_url valid for 1 hour. Opening the link on an iPhone shows "Add to Apple Wallet". Passes install on any iOS version; the iOS 26/27 layouts fall back to the classic style on older iPhones. Barcodes: QR, PDF417, Aztec and Code128 on every iOS version; Code39, Codabar, EAN13 and ITF on iOS 27+. The barcode encodes exactly barcode_message. Gate and till scanners read that data, so a copy of an existing boarding pass, ticket or loyalty card only scans if barcode_message is the original barcode's content (airline boarding passes are usually PDF417 or Aztec, holding an IATA BCBP string such as "M1DOE/JANE ..."). This tool does not issue tickets, check anyone in, or contact airlines or venues. The link must be opened in Safari on the iPhone: Wallet adds a pass from Safari, but not from a .pkpass file handed over by another app. Google Wallet on Android also imports these files. Not supported: NFC passes. With updatable=True the pass can be changed later with update_wallet_pass, and copies already in Wallet refresh themselves. Its contents are then stored on this server for updatable_hours (1 hour by default, at most 30 days), then deleted. Returns {download_url, expires_in_seconds, serial_number, pass_type_identifier}, plus edit_token and updatable_until when updatable=True, and x402_setup (how to set up x402 payments, worth passing on to the user) when x402_ready=False. Pricing: a call is one create or one update. Free for 30 calls a day per caller IP (20 from 2026-11-18), while a shared pool of 500 free calls a day lasts; failed calls count too, and counts reset at 00:00 UTC. Past either limit, a call costs $0.01 in USDC on Base, paid with x402; the refusal carries the payment requirements, and a paid result includes the payment receipt. Payment is settled only after the pass is built, so a failed build is never charged. Args: style: one of "boardingPass", "eventTicket", "coupon", "generic", "storeCard". organization_name: shown as the pass issuer. description: accessibility description (required by Wallet, not usually shown). logo_text: text shown next to the logo image. transit_type: only for style="boardingPass" -- "Air", "Boat", "Bus", "Generic", or "Train" (default "Air"). barcode_message: raw text/data encoded into the barcode. Omit for no barcode. barcode_format: a format name or an ordered list of them; each becomes a barcode with the same message, and Wallet shows the first one the device supports. Nothing is added that you don't list. Formats: "QR" (default), "PDF417", "Aztec", "Code128" (all iOS versions), and iOS 27+ only: "Code39", "Codabar", "EAN13", "ITF" -- older iPhones skip these, so e.g. ["EAN13", "Code128"] shows EAN13 on iOS 27 and Code128 before it. EAN13 needs 12-13 digits, ITF an even number of digits, Code39 uppercase letters/digits. barcode_alt_text: human-readable text shown under the barcode (e.g. the card number). background_color / foreground_color / label_color: hex colors, e.g. "#1a1a19". relevant_date / expiration_date: ISO 8601 timestamps. locations: up to 10 places where the pass appears on the lock screen when the iPhone is nearby, each {"latitude": float, "longitude": float, "altitude": optional float, "relevantText": optional str shown on the lock screen, e.g. "Your gym card"}. Look up the coordinates of the actual branch, not just the brand. For boardingPass and eventTicket the pass is relevant near a location around relevant_date if one is set; the other styles use location alone. Wallet only shows a pass within its own default radius of a location, which is small for store cards and coupons. max_distance: meters; shrinks the default radius around every location (Wallet uses the smaller of the two, so it cannot enlarge it). Requires locations. voided: mark the pass voided/used (shows a "VOID" stamp). primary_fields / secondary_fields / auxiliary_fields / header_fields / back_fields: lists of {"key": optional str, "label": optional str, "value": str, "changeMessage": optional str} shown on the pass. changeMessage only matters on updatable passes: when an update changes that field's value, the iPhone shows it as a lock-screen notification, with %@ replaced by the new value (e.g. "You now have %@ points"); without %@ Wallet shows a generic message. Updates match fields by key, so give fields that will change an explicit key (auto keys are by position). serial_number: unique id for this pass; auto-generated if omitted. icon_color / icon_text: control the auto-generated icon (a colored square with initials) when icon_png_b64 is not supplied. logo_color: color of the auto-generated logo image, a wordmark of logo_text (or organization_name) drawn on a transparent background over background_color. Defaults to icon_color. Wallet also renders logo_text as text beside the logo image, so the generated wordmark repeats it -- set generate_logo=False to show only the text. icon_png_b64 / logo_png_b64: PNG to use instead of auto-generated art. Every *_png_b64 parameter takes either base64 PNG data or an https:// URL of an image (PNG, JPEG, WebP or GIF, up to 5 MB; non-PNG is converted to PNG). The URL is fetched once, when the pass is built. generate_logo: set False to include no auto-generated logo or primary logo at all (both are optional in Wallet; a supplied logo_png_b64/primary_logo_png_b64 is still used). poster: (iOS 27+) render as Apple's new full-bleed "Poster Generic" layout -- large background image, header field, up to 4 primary fields, up to 2 footer_fields, and a square QR code. Only for style "generic", "storeCard" or "coupon"; that style is kept as the fallback older iPhones display (secondary/auxiliary fields only show on the fallback). Good for memberships, loyalty cards and gift cards. footer_fields: up to 2 fields along the bottom of a poster pass (requires poster=True). background_png_b64: base64 PNG poster background, ideally 1035x1515 px (345x505pt @3x); a gradient in background_color is generated if omitted. Only used when poster=True. featured_actions: (iOS 27+) up to 2 tappable shortcut cards shown under the pass, each {"type": ..., "url": "https://..."}. type is one of: viewSchedule, watchTrailer, listenToMusic, call (url must be "tel:+..."), addToBalance, order, shop, membershipBenefits, bookAppointment, bookCar, bookFlight, bookStay, viewOffersRewards. Works on every style; ignored by older iPhones. semantics: machine-readable tags (Apple's SemanticTags) that Wallet uses for Siri/Maps/ Calendar suggestions on every style, and to lay out the semantic designs below. Values are emitted as given; unknown keys and wrong types are rejected. Dates are ISO 8601 with an offset. Common shapes: passengerName {"givenName", "familyName"}; flightNumber is a number (123, not "AI123"); seats [{"seatNumber", "seatRow", "seatSection", ...}]; venueLocation {"latitude", "longitude"}; totalPrice {"amount": "12.50", "currencyCode": "INR"}; eventType one of generic, livePerformance, movie, sports, conference, convention, workshop, socialGathering. semantic_layout: use Wallet's semantic design, with the classic style kept for older iPhones -- which only show primary/secondary/auxiliary fields, so still fill those. - boardingPass (iOS 26+, airline only, transit_type "Air"): live flight status, gate changes, badges. Requires semantics airlineCode, flightNumber, departureAirportCode, departureCityName, destinationAirportCode, destinationCityName, originalBoardingDate, originalDepartureDate, originalArrivalDate, passengerName, plus departure and destination time zones (IANA, e.g. "Asia/Kolkata"). Apple's docs call these departureLocationTimeZone/destinationLocationTimeZone but Apple's pass-builder code uses departureAirportTimeZone/destinationAirportTimeZone; either is accepted, and giving both is safest. - eventTicket (iOS 26+ "poster event ticket"): requires eventName, venueName, venueRegionName, venueRoom; sports also needs awayTeamAbbreviation and homeTeamAbbreviation, livePerformance needs performerNames. Apple says this design is meant for NFC entry, not barcodes, and NFC passes need an Apple entitlement this server doesn't have -- Wallet may show the classic event ticket instead. info_links: top-level links that fill the event guide (event tickets) or the airline and services page (boarding passes). URL keys (http/https): accessibilityURL, addOnURL, bagPolicyURL, merchandiseURL, orderFoodURL, parkingInformationURL, purchaseParkingURL, sellURL, transferURL, transitInformationURL, contactVenueWebsite, directionsInformationURL, changeSeatURL, entertainmentURL, purchaseAdditionalBaggageURL, purchaseLoungeAccessURL, purchaseWifiURL, upgradeURL, managementURL, registerServiceAnimalURL, reportLostBagURL, requestWheelchairURL, transitProviderWebsiteURL. Text keys: contactVenueEmail, contactVenuePhoneNumber, transitProviderEmail, transitProviderPhoneNumber. Extra images (base64 PNG or https URL). Which image shows where depends on style and iOS version (from Apple's Pass Designer docs); Wallet ignores an image a layout has no slot for: primary_logo_png_b64: max 126x30pt. Boarding pass and coupon on iOS 27+, event ticket on iOS 18+, poster. On those, the plain logo is only shown by older iOS. A wordmark is auto-generated for poster and semantic_layout passes unless generate_logo=False. secondary_logo_png_b64: max 135x12pt. Event tickets, iOS 18+. strip_png_b64: 375x144pt banner behind the primary fields. Coupon, store card and event ticket; not shown on iOS 26+ coupon/store card. thumbnail_png_b64: 90x90pt. Generic and event ticket. artwork_png_b64: 358x448pt poster event ticket artwork (eventTicket with semantic_layout, iOS 27+); if neither this nor background_png_b64 is given, a gradient in background_color is generated, since Wallet needs one of them. background_png_b64 is also used on eventTicket (blurred behind the classic ticket). updatable: keep this pass on the server so update_wallet_pass can change it later. The response then includes an edit_token: the only way to update the pass, and it can't be recovered, so give it to the user. Wallet registers each iPhone that adds the pass, and an update reaches them within seconds. The pass contents are stored (other passes only log the style and organization_name). Use for passes that change: loyalty points, gate or seat changes, memberships that can be cancelled. updatable_hours: how long an updatable pass can be updated, 1 (default) to 720 (30 days), counted from creation; updates don't extend it. Afterwards the stored pass is deleted and can't be changed again, while copies in Wallet stay as they last were. Pick it to cover the pass's useful life, e.g. until a flight lands or an event ends. Only with updatable=True. contact_email: required. The user's address, so the operator of this service can reach them about it, for example if it changes or breaks for them. Ask the user for it; never take it from the pass details or make one up. It isn't added to the pass, and it's kept in the request log. x402_ready: required. True if this client can pay with x402, False if it can't, "unknown" if you don't know. It shows the operator how many clients could pay past the free limit. Only logged: it changes neither price nor limits.
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  • 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 1866 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 7,188 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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  • Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob (mid), forecast_prob, and edge_pp per strike, plus the settlement clause verbatim. BACKTEST (`backtest_days: N`): scores an archived gridded forecast against the market on settled days and returns brier_market vs brier_forecast with a plain-English `verdict`, so the edge is MEASURED rather than asserted. READ THE WARNINGS — they are not boilerplate. (1) These markets DO NOT settle on the NWS. They settle on The Weather Company (weather.com) at a Kalshi station code such as CLINYC, which the response quotes verbatim; so part of every edge_pp is NWS-vs-Weather-Company disagreement about the same day at the same station, which is not mispricing and not tradeable. `settlement_vs_forecast_basis_f` from backtest mode is that part as a number. (2) The station is DERIVED from the settlement clause, never from the city name: Chicago settles at MIDWAY and New York at CENTRAL PARK, so a city-centre forecast would misprice a whole ladder. A station that cannot be resolved yields rows with no forecast and a reason, never a guessed coordinate. (3) forecast_prob assumes a normal distribution around the NWS high whose width is ASSUMED, not fitted (stated in `distribution_assumption`) — run backtest mode to see whether it is calibrated. (4) edge_pp is gross: no Kalshi fees, no bid-ask. MEASURED RESULT, AND IT IS NOT THE FLATTERING ONE: on the first backtest (KXHIGHNY, 13 settled days to 2026-09-11, 58 market observations) the MARKET beat the forecast — Brier 0.1008 for the market against 0.1594 for the archived gridded forecast, lower being better. So on that sample there is NO forecast edge to sell, and a large edge_pp is more likely to be the model disagreeing with a better-informed market than an opportunity. The measured settlement-vs-forecast basis was 1.7F mean absolute over 8 pinnable days, slightly warm-biased, which is a big share of a typical edge_pp on a 2-degree bracket. Re-run backtest_days before believing any edge; if a later sample reverses this, the numbers say so. NWS is US-only, so the ~30 international Kalshi weather series (London, Paris, Tokyo) return market prices with forecast_unavailable rather than a forecast. Precipitation series are listed but not yet priced. Cities: nyc, chicago, los angeles, miami, austin, houston, denver, philadelphia — or pass `series_ticker` for any other (e.g. "KXHIGHTBOS").
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  • Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code independently verified the model's quote is a VERBATIM substring of text actually fetched; "inferred" means a value was given but the quote could not be verified; "not_established" means no source answered the field, and its value is always null — never guessed, never a blended score. Sources: "web" fetches the company's own site (entity.domain required — homepage, /about, /leadership) via fetch_url; "catalog" checks entity_profile (SEC EDGAR; resolved:false for a private company is expected, not a failure); "both" (default) tries both. max_cost (USD, default 0.02, max 0.50) scales how many pages are fetched and refuses up front if it is too small to pay for even one extraction call (floor $0.002) — never silently overspends. A row where every source comes back empty costs nothing: every field is mechanically not_established with NO model call made. For a boolean/derived field (e.g. "does this company sell to healthcare"), the quote only has to SUPPORT the value — a descriptive sentence about customers/products counts, the source need not state the answer verbatim. leadership_page_status ("fetched"|"not_found"|"not_attempted", plus leadership_note) says plainly whether a leadership/team page was actually read, so a named-person field (head_of_sales) coming back not_established is distinguishable from "this company just doesn't publish one" vs. "we never checked". model_output_empty:true means the model returned nothing usable (a transport/budget problem) — every field is not_established for THAT reason, never read as 20 individual "no" judgments. Use with a fixed question + schema across many rows for "Claygent over N companies with a hard cost cap" (composes with batch callers). For picking from a fixed label list instead of extracting open fields, use classify_row (cheaper, one model call).
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  • Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.
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  • 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 1866 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 7,188 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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  • Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob (mid), forecast_prob, and edge_pp per strike, plus the settlement clause verbatim. BACKTEST (`backtest_days: N`): scores an archived gridded forecast against the market on settled days and returns brier_market vs brier_forecast with a plain-English `verdict`, so the edge is MEASURED rather than asserted. READ THE WARNINGS — they are not boilerplate. (1) These markets DO NOT settle on the NWS. They settle on The Weather Company (weather.com) at a Kalshi station code such as CLINYC, which the response quotes verbatim; so part of every edge_pp is NWS-vs-Weather-Company disagreement about the same day at the same station, which is not mispricing and not tradeable. `settlement_vs_forecast_basis_f` from backtest mode is that part as a number. (2) The station is DERIVED from the settlement clause, never from the city name: Chicago settles at MIDWAY and New York at CENTRAL PARK, so a city-centre forecast would misprice a whole ladder. A station that cannot be resolved yields rows with no forecast and a reason, never a guessed coordinate. (3) forecast_prob assumes a normal distribution around the NWS high whose width is ASSUMED, not fitted (stated in `distribution_assumption`) — run backtest mode to see whether it is calibrated. (4) edge_pp is gross: no Kalshi fees, no bid-ask. MEASURED RESULT, AND IT IS NOT THE FLATTERING ONE: on the first backtest (KXHIGHNY, 13 settled days to 2026-09-11, 58 market observations) the MARKET beat the forecast — Brier 0.1008 for the market against 0.1594 for the archived gridded forecast, lower being better. So on that sample there is NO forecast edge to sell, and a large edge_pp is more likely to be the model disagreeing with a better-informed market than an opportunity. The measured settlement-vs-forecast basis was 1.7F mean absolute over 8 pinnable days, slightly warm-biased, which is a big share of a typical edge_pp on a 2-degree bracket. Re-run backtest_days before believing any edge; if a later sample reverses this, the numbers say so. NWS is US-only, so the ~30 international Kalshi weather series (London, Paris, Tokyo) return market prices with forecast_unavailable rather than a forecast. Precipitation series are listed but not yet priced. Cities: nyc, chicago, los angeles, miami, austin, houston, denver, philadelphia — or pass `series_ticker` for any other (e.g. "KXHIGHTBOS").
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  • Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code independently verified the model's quote is a VERBATIM substring of text actually fetched; "inferred" means a value was given but the quote could not be verified; "not_established" means no source answered the field, and its value is always null — never guessed, never a blended score. Sources: "web" fetches the company's own site (entity.domain required — homepage, /about, /leadership) via fetch_url; "catalog" checks entity_profile (SEC EDGAR; resolved:false for a private company is expected, not a failure); "both" (default) tries both. max_cost (USD, default 0.02, max 0.50) scales how many pages are fetched and refuses up front if it is too small to pay for even one extraction call (floor $0.002) — never silently overspends. A row where every source comes back empty costs nothing: every field is mechanically not_established with NO model call made. For a boolean/derived field (e.g. "does this company sell to healthcare"), the quote only has to SUPPORT the value — a descriptive sentence about customers/products counts, the source need not state the answer verbatim. leadership_page_status ("fetched"|"not_found"|"not_attempted", plus leadership_note) says plainly whether a leadership/team page was actually read, so a named-person field (head_of_sales) coming back not_established is distinguishable from "this company just doesn't publish one" vs. "we never checked". model_output_empty:true means the model returned nothing usable (a transport/budget problem) — every field is not_established for THAT reason, never read as 20 individual "no" judgments. Use with a fixed question + schema across many rows for "Claygent over N companies with a hard cost cap" (composes with batch callers). For picking from a fixed label list instead of extracting open fields, use classify_row (cheaper, one model call).
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  • Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.
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  • 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 1866 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 7,188 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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  • Prices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob (mid), forecast_prob, and edge_pp per strike, plus the settlement clause verbatim. BACKTEST (`backtest_days: N`): scores an archived gridded forecast against the market on settled days and returns brier_market vs brier_forecast with a plain-English `verdict`, so the edge is MEASURED rather than asserted. READ THE WARNINGS — they are not boilerplate. (1) These markets DO NOT settle on the NWS. They settle on The Weather Company (weather.com) at a Kalshi station code such as CLINYC, which the response quotes verbatim; so part of every edge_pp is NWS-vs-Weather-Company disagreement about the same day at the same station, which is not mispricing and not tradeable. `settlement_vs_forecast_basis_f` from backtest mode is that part as a number. (2) The station is DERIVED from the settlement clause, never from the city name: Chicago settles at MIDWAY and New York at CENTRAL PARK, so a city-centre forecast would misprice a whole ladder. A station that cannot be resolved yields rows with no forecast and a reason, never a guessed coordinate. (3) forecast_prob assumes a normal distribution around the NWS high whose width is ASSUMED, not fitted (stated in `distribution_assumption`) — run backtest mode to see whether it is calibrated. (4) edge_pp is gross: no Kalshi fees, no bid-ask. MEASURED RESULT, AND IT IS NOT THE FLATTERING ONE: on the first backtest (KXHIGHNY, 13 settled days to 2026-09-11, 58 market observations) the MARKET beat the forecast — Brier 0.1008 for the market against 0.1594 for the archived gridded forecast, lower being better. So on that sample there is NO forecast edge to sell, and a large edge_pp is more likely to be the model disagreeing with a better-informed market than an opportunity. The measured settlement-vs-forecast basis was 1.7F mean absolute over 8 pinnable days, slightly warm-biased, which is a big share of a typical edge_pp on a 2-degree bracket. Re-run backtest_days before believing any edge; if a later sample reverses this, the numbers say so. NWS is US-only, so the ~30 international Kalshi weather series (London, Paris, Tokyo) return market prices with forecast_unavailable rather than a forecast. Precipitation series are listed but not yet priced. Cities: nyc, chicago, los angeles, miami, austin, houston, denver, philadelphia — or pass `series_ticker` for any other (e.g. "KXHIGHTBOS").
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  • Claygent-style per-row research: answer ONE question about ONE company and return a JSON object matching your output_schema, with every field wrapped in its own evidence — {value, evidence_url, quote, status}. status is NEVER self-reported by the model: "found" means this code independently verified the model's quote is a VERBATIM substring of text actually fetched; "inferred" means a value was given but the quote could not be verified; "not_established" means no source answered the field, and its value is always null — never guessed, never a blended score. Sources: "web" fetches the company's own site (entity.domain required — homepage, /about, /leadership) via fetch_url; "catalog" checks entity_profile (SEC EDGAR; resolved:false for a private company is expected, not a failure); "both" (default) tries both. max_cost (USD, default 0.02, max 0.50) scales how many pages are fetched and refuses up front if it is too small to pay for even one extraction call (floor $0.002) — never silently overspends. A row where every source comes back empty costs nothing: every field is mechanically not_established with NO model call made. For a boolean/derived field (e.g. "does this company sell to healthcare"), the quote only has to SUPPORT the value — a descriptive sentence about customers/products counts, the source need not state the answer verbatim. leadership_page_status ("fetched"|"not_found"|"not_attempted", plus leadership_note) says plainly whether a leadership/team page was actually read, so a named-person field (head_of_sales) coming back not_established is distinguishable from "this company just doesn't publish one" vs. "we never checked". model_output_empty:true means the model returned nothing usable (a transport/budget problem) — every field is not_established for THAT reason, never read as 20 individual "no" judgments. Use with a fixed question + schema across many rows for "Claygent over N companies with a hard cost cap" (composes with batch callers). For picking from a fixed label list instead of extracting open fields, use classify_row (cheaper, one model call).
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  • Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.
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  • 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 1866 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 7,188 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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