"H&M" matching MCP tools:

• query_tasks

  cnvs.app

  Read tasks from a 'todo' board with server-side filtering — handy for 'what's overdue?' / 'what's assigned to X?' without pulling the whole board. All filters are optional and AND together: `assignee` (exact match), `priority` ('H'|'M'|'L'), `done` (boolean), `overdue` (true → due_date strictly before today, not done), `due_before` / `due_after` (ISO date window on due_date). Returns `{ boardId, mode, tasks }` — tasks ordered by sort, each with the same fields as `list_tasks`.

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• noaa_get_meteorological_data

  NOAA Tides and Currents

  Get observed meteorological/oceanographic sensor data from a NOAA station. Products: air_temperature, water_temperature, wind (speed/gust/direction), air_pressure, air_gap (bridge clearance to water surface), conductivity, visibility, humidity, salinity. Units by system: temps °F/°C; wind knots (english) or m/s (metric); air_gap feet/meters; visibility nautical miles/kilometers; air_pressure always millibars; salinity always PSU. Max span ~31 days per request; interval "6" (6-minute, default) or "h" (hourly). Not every station has every sensor — check with noaa_get_station_info (expand ["sensors"]). Water-level data is served by noaa_get_water_levels, not this tool.

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• au_water

  dynamic-feed

  Australian river heights + gauge rainfall near any AU location — live CC-BY-licensed gauge observations from the Bureau of Meteorology's Water Data Online (keyless KiWIS API); the Australian counterpart of water_levels (US USGS). Per station: latest river level (m) with a ~3 h rising/falling/steady trend, or rainfall totals (mm over 1/6/24 h ending at the latest reading), plus real observation timestamps + ages, distance, the data owner and the exact attribution string. `location` = an AU preset ("brisbane" default, "sydney", "melbourne", "adelaide", "hobart", "darwin", "canberra", "perth") or a "lat,lon" string; explicit `lat`/`lon` override. `kind` = "river" | "rain" | "both". Only stations whose data owner is CC-BY-listed (Table 1) in the BoM rain/river licensing statement are served — per-station owner attribution carried in provenance, exclusion counts reported, WA coverage honestly partial. Observational data ONLY — not a flood warning product; official flood warnings/watches are issued by the Bureau at bom.gov.au/australia/warnings. Every value is returned in an Ed25519-signed, provenance-stamped envelope (source and observation time) you can verify offline against /.well-known/keys, no account required.

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• maps_distance_matrix

  Google_maps

  "Travel time matrix between [N] origins and [M] destinations" / "drive-time grid via Google Maps" / "transit times between addresses" — N×M distance and duration matrix between many points via Google Maps. Modes: driving, walking, bicycling, transit. Use for delivery routing, multi-stop optimization, transit-heavy planning.

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• report_get

  Kash.click

  Download a synthetic HTML sales report for a given period. Period logic: omit all date fields to get yesterday's report; provide y only for a full-year report; y + m for a full-month report; y + m + d for a specific day. Returns an HTML summary including total revenue, number of orders, breakdown by department, VAT summary, and payment methods.

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• explain_queueing_theory

  QueueSim

  Return a ~500-word educational explainer of M/M/c queueing theory: Little's Law, utilization, why averages mislead, how simulation relates to Erlang-C. No inputs. Use this when the user asks a conceptual 'why' or 'how does this work' question rather than asking for a number.

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• get_stops_around_location

  Lviv Public Transport

  Discovers transit stops near a geographic point, returning each stop's numeric code, name, coordinates, and walking distance. Also emits a map UI block with multiple markers for map-capable clients (e.g. ChatGPT). Use this as the **first step** whenever the user provides an address, place name, or coordinates and you need stop IDs before calling `get_stop_realtime` or `get_stop_geometry`. Do NOT use this to fetch arrivals or live vehicle data — it returns stop metadata only. Default radius is 1 000 m; narrow it (e.g. 300 m) for dense urban areas or widen it (up to 3 000 m) for rural locations.

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• wake_ai_always_on_channel

  H/M Blindspot Challenge Platform

  Idempotently checks or restores the fixed H/M 24/7 channel and returns only public status. Stream credentials and private capabilities are never returned.

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• prepare_attachment_upload

  linear

  Prepare a direct Linear file upload for an existing issue. Workflow: 1. Call this tool with issue, filename, contentType, and size. 2. Upload raw bytes with PUT to uploadRequest.url outside MCP. 3. All headers in uploadRequest.headers are part of the signed request, so send them verbatim. 4. After PUT succeeds, call create_attachment_from_upload with assetUrl to link it to the issue. Do not base64-encode or transform the file. Use curl --data-binary @path or fetch(url, { method: 'PUT', body: blob }). Omitting or modifying any signed header, including casing, will return HTTP 403. The signed URL must be used within 60 seconds or it will expire. Upload sequencing: Prepare, PUT, and finalize one file before calling this tool for another file. Do not batch multiple prepare_attachment_upload calls before starting the PUTs because earlier signed URLs can expire while later files are prepared. Example: curl -X PUT --data-binary @file.png \ -H "content-type: image/png" \ -H "x-goog-content-length-range: N,N" \ -H "cache-control: public, max-age=31536000" \ -H 'Content-Disposition: attachment; filename="file.png"' \ "<uploadRequest.url>"

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• compare_analytical_vs_simulated

  QueueSim

  Run the same M/M/c configuration through BOTH the closed-form Erlang-C formula AND the discrete-event simulator, returning a side-by-side comparison with deltas. Use this when the user is validating QueueSim's engine against textbook values, learning queueing theory by watching simulation converge on the formula, or auditing a result that 'feels off' — agreement within ~5%% is the canonical sanity check for an M/M/c run. Pure-Exponential M/M/c only; the closed-form Erlang-C is undefined for other service distributions. Large deltas usually mean the simulation run was too short for steady-state — raise simulationDays. ANTI-FABRICATION: both sides come from real computation — closed-form is deterministic, simulation is stochastic but engine-backed. Quote both verbatim. Do not synthesize an 'average of the two' or recompute the formula from training-data recall.

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• safe_exposure_time

  decibel-shield

  Answers "how long can I listen to 100 dB", "is 85 dB dangerous for 8 hours", "how long at a concert before hearing damage". Maximum daily safe exposure time for a sound level per NIOSH's recommended exposure limit: 85 dB(A) for 8 h, 3 dB exchange rate (88 dB → 4 h, 100 dB → 15 min). Input is a dB number; to get the dB of a named sound first, use lookup_sound_level.

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• strftime_preview

  mcp

  Use this when you need to know exactly what a C/POSIX strftime pattern (%Y %m %d %H %M %S %A %B %j %z etc.) produces. Prefer this over guessing the output yourself. Deterministic: same input, same output; the reference time is formatted in UTC (%Z is 'UTC', %z is '+0000', defaults to current time when datetime is omitted). Unknown directives pass through literally. Example: {format:'%A, %B %e, %Y at %I:%M %p', datetime:'2026-07-08T14:30:45'} -> 'Wednesday, July 8, 2026 at 02:30 PM'.

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• window_set_frame

  local-mcp

  Pins a window (by window_id) to fixed bounds {x,y,w,h} in global points, so every take is framed identically across runs. Returns the actual post-constraint bounds. Requires Accessibility permission.

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• unlock_blindspot_dossier

  H/M Blindspot Challenge Platform

  Unlocks the integrity-committed synthetic Blindspot evaluation dossier after exact x402 settlement. Returns the decision-changing variable, evidence rubric, strongest contradiction and reversal condition.

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• get_insider

  Edgrapi — SEC EDGAR Financials

  Parsed SEC Form 4 insider trades for a ticker: owner, role, transaction code (P open-market purchase, S sale, A award, M exercise, F tax withholding), shares, price, dollar value, and a 10b5-1 plan flag. Code P is the only own-money buy signal; A/M/F are automatic compensation.

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• explain_advanced_patterns

  QueueSim

  Return a textbook-level description of six queueing complexity patterns beyond basic M/M/c: abandonment/reneging, priority tiers, overflow routing, skills-based routing, compound service, and server outages. Use this when the user describes real-world complexity (customers hanging up, VIP queues, specialist escalation, agent breaks, transfers) that plain M/M/c doesn't model. The tool frames each pattern conceptually and points users at ChiAha for custom modeling.

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• interpret_result

  QueueSim

  Given an M/M/c configuration (arrivalRate, serviceRate, servers) and optionally an observed average wait, returns a queueing-theory framed interpretation: where you sit on the utilization curve, what ρ means in plain language, what one more or fewer server would qualitatively do, and which complexity factors (priority, abandonment, skills routing) might be hiding in real data the M/M/c model can't see. Use this to TEACH while answering — when the user wants context around a number, not just the number itself. Pure text computation, no simulation, no RNG — deterministic output.

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• summary

  Biorxiv

  bioRxiv submission/publication counts. Interval: "m" (monthly, default) or "y" (yearly). bioRxiv only — medRxiv has no /sum endpoint.

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• explain_ed_queueing

  QSimHealth

  Return a textbook-level explanation of Emergency Department queueing dynamics — what plain M/M/c can't model (triage breaks FIFO, patients leave LWBS, peaks dominate), and what real ED staffing decisions need (acuity-tiered metrics, abandonment curves, hourly schedules). Use this when the user asks conceptual questions about ED waits or staffing.

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• about_mkliniki

  mkliniki

  What M-Kliniki is, the services it offers in Kenya, and how its escrow payments work. Call this to describe M-Kliniki accurately to a user.

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