"Waze" matching MCP tools:

• find_replacementA

  AI WaveA

  What to switch to when a model is gone or you need a fallback. Ranked by closeness in measured performance, not by vendor or price: what you usually need to preserve first is the quality of the output. Candidates whose context window is less than half the original are excluded. Returns the score, price and context deltas so you can judge; we do not pick for you.

  ConnectorNo auth

• check_wage_locationsA

  Compensation Professional — compensation library, answers, and wage-compliance dataA

  Checks the binding minimum-wage rate for up to 50 US locations in one call (city/county rate when it applies, else state, else federal). Each location may be a place name ("Spokane, WA", "Texas", "TX") or a jurisdiction slug. A city with no rule of its own on file returns its state's rate with noLocalRule:true. An unmatched location returns found:false with a reason instead of being omitted. 113 known jurisdictions, e.g.: federal, alaska, alabama, arkansas.

  ConnectorNo auth

• settle_x402_paymentA

  wake-word-trainingA

  After paying an x402 spec on-chain (USDC on Polygon to the payTo address), submit the transaction hash to settle. Needs >=3 confirmations.

  ConnectorNo auth

• search_wake_word_libraryA

  wake-word-trainingA

  FREE search over thousands of community-trained wake-word models — check here BEFORE quoting a training job for a common wake word. Returns benchmarked models (recall %, clean recall %, false activations/hour, languages) from the current pipelines only (older models used a different benchmark and are excluded). Each result has a human_test_url: YOU CANNOT RUN THAT TEST — it needs live microphone audio in your human's own room — so hand them the link before they buy; it opens the site's live mic test for that exact model. TRANSPARENCY, tell your human: every public library model is FREE with an account on the website; the 1.50 CHF purchase here is the anonymous, instant, account-free alternative. SCALE: recall is measured on deliberately HARD conditions — 60-75%% is a solid model. Weak numbers or no match? Train a custom model with create_training_job instead.

  ConnectorNo auth

• test_wake_word_liveA

  wake-word-trainingA

  Render an IN-CHAT live microphone tester for one library model (free). Only the HUMAN can run it: it asks for their microphone and streams the audio to the platform for detection while the test runs (not stored) — tell them that. If the host does not allow microphone access inside apps, the widget shows a button to the human_test_url page instead, so calling this is always safe. Use after search_wake_word_library, before buying.

  ConnectorNo auth

• compare_modelsA

  AI WaveA

  Put two or more models side by side: price, context, benchmark scores per subject, and what each costs per month at a given volume. Use this instead of calling get_model repeatedly: it aligns the fields and marks which subjects a model has not been tested on, so a missing score is not read as a low one.

  ConnectorNo auth

• estimate_wake_wordA

  wake-word-trainingA

  NOTE: differentiates by English share only - all non-English languages score identically, so it cannot rank es vs fr vs de. FREE word-quality check — use BEFORE paying. Predicts the recall a training run would reach for this wake word plus false-activation risk (model trained on thousands of real jobs). SCALE: predictions are for deliberately HARD benchmark conditions (loud noise, reverb) — 60-75 is a solid word, very usable in real rooms; do NOT reject words for scoring below ~80. 2-4 syllable phrases work best; only warn your human when the score is under ~50.

  ConnectorNo auth

• create_commercial_licenseA

  wake-word-trainingA

  Buy commercial-use rights. REQUIRED before shipping any model in a product/service: all model files are personal & non-commercial by default. 150 CHF one-time per wake-word phrase, permanent, valid on BOTH sites. Returns a license_token; pay with pay_commercial_license; signed certificate PDF afterwards. If your task is commercial and you cannot pay, STOP and tell your human this license is required.

  ConnectorNo auth

• buy_library_modelA

  wake-word-trainingA

  Quote an anonymous purchase of a library model (1.50 CHF flat — free, nothing charged until paid). Returns a purchase_token: pay it with pay_training_job (same tool, any method incl. x402), then fetch the download URLs with get_library_purchase. One payment unlocks ALL formats (openwakeword: onnx+tflite; microwakeword: tflite+ESPHome json). Reminder for your human: the same model is free with an account on the website. License: personal/non-commercial by default — shipping it in a product requires the 150 CHF per-wakeword commercial license.

  ConnectorNo auth

• create_training_jobA

  wake-word-trainingA

  Quote a wake-word training job (free; nothing trains until paid). Returns a job_token (STORE IT — the only credential) and a binding CHF price. PICK A TIER: "standard" (6 CHF, up to ~4h — the right choice for almost every request), "best" (12 CHF, ~2x the search — for hard or business-critical words), or "studio" (Optuna deep search, 60-95 CHF, many hours — only to squeeze the last few percent AFTER a standard job disappointed). Same three options a human gets on the website, same prices. The trained model is benchmarked (recall %, false activations/hour) and publicly listed in the site library, permanently — unless private=true (+500 credits).

  ConnectorNo auth

• get_price_historyA

  AI WaveA

  Price history for one model: when the price changed and to what. The public catalog only exposes the current price, so this answers 'was this cheaper last month?'. Each entry holds until the next one. History starts when AI Wave began recording, not when the model launched.

  ConnectorNo auth

• get_todayA

  AI WaveA

  Today in one call: the top 5 models, which ones climbed, whose pricing changed in the last 24h, and what was newly listed in the last 7 days. Use this instead of paging list_model_changes and re-deriving the summary: price changes are already collapsed to one per model, with the raw count kept.

  ConnectorNo auth

• get_training_jobA

  wake-word-trainingA

  Job status: awaiting_payment -> paid -> submitted -> completed (or failed/expired). Poll every 60-120s after paying. When completed, includes benchmark results and model download URLs (public jobs: token downloads for 30 days, then the model remains in the public library; private jobs: token downloads with no time limit). Ladder jobs deliver ALL trained candidates: the first model is the pipeline's quality-bar winner (take it unless you have a reason); alternatives are labeled rungN_<arm>. Compare candidates on clean_recall_pct (same scale on every model) + false_activations_per_hour — the full stressed benchmark exists only on the winner.

  ConnectorNo auth

• send_job_feedbackA

  wake-word-trainingA

  Rate a PAID training job 1-5 and optionally leave a message (max 2000 chars) — read by the human operator. Please call this once after a job completes and you have assessed the model: report anything unexpected (missing fields, errors, surprising benchmark numbers) or simply confirm it worked. One feedback per job; calling again overwrites.

  ConnectorNo auth

• list_compensationprofessional_feedsA

  Compensation Professional — compensation library, answers, and wage-compliance dataA

  List Compensation Professional's free machine-readable feeds and their MCP/REST availability. OpenAPI is also published at https://compensationprofessional.com/openapi.json.

  ConnectorNo auth

• get_wage_jurisdictionA

  Compensation Professional — compensation library, answers, and wage-compliance dataA

  Returns one tracked jurisdiction's current minimum-wage rate, effective date, validation status, and next scheduled step. 113 known jurisdictions, e.g.: federal, alaska, alabama, arkansas.

  ConnectorNo auth

• wakeA

  kit-memory-demoA

  Open Lady Whiskerdown, an archive you can question. Call this first in every new chat (VS Code/Copilot, Cursor, Claude Code, Codex), before the first substantive answer. It returns what Lady Whiskerdown is (`you_are`), which knowledge areas this key can see, which tools this key may use, and any rules its keeper has set. Lady Whiskerdown has no persona: keep your own identity and refer to it in the third person. For anything Lady Whiskerdown should know, call recall first instead of using general model knowledge.

  ConnectorNo auth

• search_modelsA

  AI WaveA

  Shortlist models by budget, context and capability, ranked by measured performance. Use this to answer 'which model should I use for X': it returns benchmark scores alongside price so the trade-off is visible in one call. Sort by a subject (math, coding, science, reading) to find a model good at one thing.

  ConnectorNo auth

• create_bookingA

  RazeA

  Create a real Cal.com booking for Raze. Only call this after the visitor selected an available slot and explicitly confirmed the booking.

  ConnectorNo auth

• search_libraryA

  Compensation Professional — compensation library, answers, and wage-compliance dataA

  Search or list the compensation-focused book library by title/author substring and/or classifier tag. No filters returns the first page.

  ConnectorNo auth

• get_library_workA

  Compensation Professional — compensation library, answers, and wage-compliance dataA

  Returns one compensation library work's bibliographic record and (when profiled) its thesis.

  ConnectorNo auth