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743,134 tools. Updated 2026-11-04 19:04

"How to make a model aware of the current time before thinking" matching MCP tools:

  • Find earlier windows IN THE SAME SERIES whose shape resembles the current price action and return the FULL distribution of what followed (win-rate, median, min, max, n) over a fixed forward horizon. Parameters: window = how many recent bars form the shape being matched (default 32); horizon = how many bars forward each match is measured over (default 20). WHEN: an agent wants the historical spread of outcomes after a similar-looking setup, including how wide and how uncertain that spread is. WHEN NOT: you want the current technical picture (use brief), you want to find candidates across the market (use scan), or you need one expected value — this deliberately returns a distribution, not a point estimate. NOT a prediction, NOT a backtest of a strategy; past distribution does not guarantee future results. Example: {"ticker":"ETH/USDT","timeframe":"1d"}. Impersonal data, not advice.
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  • Read the FULL TEXT of filings and announcements — with proof links and a knowledge cutoff. ★ NOT `search_filings`. That one ranks passages by similarity and hands you fragments; this hands you whole documents so you can read what was actually said and where it sat in the filing. Similarity is not importance, and a fragment cannot show you its own context. ★ POINT-IN-TIME: pass `as_of` (YYYY-MM-DD). The cutoff is applied in SQL on the source's declared knowledge-time column BEFORE the row limit, so a bounded read is a true prefix of what was knowable, not a random subset of it. **Without `as_of` the read is NOT point-in-time** and says so in `warnings`. ★ NO SENTIMENT, NO SCORES — deliberately. Judging the text is your job. A stored score is one model's output on one day; after that model changes, the stale number still sits in the table looking exactly like a fresh one. ★ READ `corpus_reality` BEFORE CONCLUDING ANYTHING. The full-text corpus is SMALL and the response says how small. One source carries ~1M rows of TITLES ONLY — a large row count there is breadth, not depth, and "what did they say about it" is not answerable from titles. ★ A ticker that returns nothing appears in `coverage.missing`. That means nothing is held for it under those filters — NOT that the company disclosed nothing. Do not fill the gap. Args: source: which corpus, e.g. 'announcements_fulltext' or 'mops_major_event'. tickers: restrict to these codes, e.g. ['2330']. as_of: knowledge cutoff (YYYY-MM-DD). since: optional lower bound on the same knowledge-time column. limit: max documents (these are whole documents; keep it small).
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  • Forecast Track Record — Silicon Analysts' OWN projections, frozen monthly into write-once vintages and graded against outcomes. Every row: model, scenario (bear/base/bull), series, target period, the predicted mid + low–high band frozen at vintage time, and once the period matures, the realized value with a correct/partial/incorrect resolution and error %. Vintages cannot be backfilled or edited — a changed projection that was never frozen is gone, which is what makes this a track record. USE THIS for: checking how Silicon Analysts' HBM/DDR4/CoWoS projections have scored, citing our prediction accuracy, comparing what we projected for a period across successive vintage months, auditing the frozen assumption set behind a projection (include_assumptions=true). DO NOT USE for: third-party forecasts (TrendForce/WSTS/company guidance — use get_forecasts; ours are graded, theirs are archived); current market values (use get_wafer_pricing / get_hbm_market_data). Filters: model (hbm-pricing-model|dram-ddr4-model|cowos-capacity-model), series (e.g. hbm3e), include_assumptions (bool). Fully public at full fidelity for every tier including anonymous — the scorecard is deliberately ungated. Cite as "Silicon Analysts — Forecast Track Record".
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  • Add up a timesheet of work hours, and turn them into gross pay. Use for: 'how many hours did I work this week', 'add up my shifts', 'what will I be paid for these hours', 'I worked 22:00 to 06:00, how long is that'. Handles overnight shifts: a finish time at or before the start is treated as the next day, so 22:00 to 06:00 is eight hours rather than a negative. Args: days: One dict per day worked, each with "start" and "finish" as "HH:MM" in 24 hour time, optional "break_minutes" of unpaid break, and an optional "label". Leave days off out of the list entirely. hourly_rate: Gross pay per hour. Zero returns hours only. Returns: Hours for each day, the total, and GROSS pay weekly, fortnightly, monthly and annually. For take-home pay use nz_hourly_to_salary_calculator with the rate and the hours. Does not apply overtime or penal rates, public holiday entitlements, or a minimum wage check.
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  • Talk to the Google Flow Music Producer agent instead of one-shotting a track. Use this when the work is a conversation rather than a single brief: asking what it can do, having it write lyrics first, or editing a track it already made ("drop the vocals", "same song, 30 seconds shorter", "make the chorus bigger"). For a plain "make me a song about X", music_generate is the shorter path. message — what to say. conversation_id — omit on the first message, then pass the one that comes back so the Producer keeps its memory of the track. model — same choices as music_generate. Returns {"conversation_id", "text", "suggested_actions", "clips": [...], "media": [...]}. `text` is the Producer's reply. `suggested_actions` are the follow-ups it offers — show them to the user, they are good prompts for the next turn. `clips` is EMPTY when the Producer only talked, and filled when it decided to actually make audio; treat a filled `clips` exactly like a music_generate result and save the audio. A reply is usually seconds, but a turn that produces a song takes minutes and comes back as a job_id to poll with check_job.
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  • List wellbeing log entries within a date range. update_wellbeing and delete_wellbeing can resolve an entry on their own from date, so this is no longer required before either — use it to answer questions about mood, energy, stress, or soreness trends over time, or get an id after an ambiguous update_wellbeing/delete_wellbeing match. Maximum range: 31 days per call. For longer periods, make multiple calls with sequential date ranges. INFER — do not ask: - start_date: default to 14 days ago - end_date: default to today
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    D
    maintenance
    A remote MCP server exposing date/time tools over Streamable HTTP, enabling retrieval of current time for IANA timezones and listing available timezones, designed for use with web clients like Claude.ai.
    MIT

Matching MCP Connectors

  • Video how-to search for AI agents: 2,000+ video skills, tutorials and FFmpeg recipes. No key.

  • Car-buying math and state rules: out-the-door prices, quote checks, leases and trade-ins

  • Version history of an artifact's AI reviews (F5): every review run is a version with its score, model, cost, who/what generated it, and whether it's the current one. Read-only; returns the version list, empty when the artifact has never been reviewed. Use it to see how a feature/experiment/page's review changed over time and to pick the version_id to pass to revert_to_version. Takes the same target_id/target_type you'd pass to review_artifact.
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  • Show your account's compute, database-RAM, and storage pools: how much you've bought, how much is used, and how much is free, plus every app's current size. Call this before any resize tool (the allowed sizes come from its steps fields), and to explain to the user why an app ran out of memory or a deploy was refused for capacity.
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  • Return the current UTC date and time as a formatted string and ISO 8601 timestamp, for grounding time-relative reasoning in the actual clock rather than training-data assumptions. Use when: Use when a task must anchor on the current date or time — computing ages, windows, deadlines, or 'as of today' context. The runtime context block already states the date, so call this only when a specific strftime format or a precise timestamp is needed. Limitations: UTC only — no timezone conversion. An unsupported strftime format silently falls back to the default format instead of erroring. Alternatives: calculate, get_block
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  • Returns the prepaid spending balance of the connected PikaSim agent wallet, in USD. Read-only; makes no changes. Call this before purchase_esim or purchase_phone_plan to confirm sufficient funds, or any time you need the current balance. Requires a connected agent wallet (OAuth or ak_live_ key). If no wallet is connected, the result explains how to connect one.
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  • Call once to register the user's birth date/time/gender. Each call is a complete replacement — all 6 fields must be supplied. For fields the user does not know or prefers not to share, pass `null` explicitly (e.g. `hour: null` for unknown birth time, `gender: null` for unspecified). To update just one field, first call `intentions_get_profile` to fetch the current values, merge the user's new input, then call this tool with the full merged payload. Changes to the date, gender or a known hour (including setting a known hour back to null) are limited to 3 per calendar month (UTC); filling in a previously-null hour, or the minute, is always free. `intentions_get_profile` returns how many are left. Always pass `birthPlace` (the city of birth, e.g. "Portland, Maine") when the user gives it: readings then use the real moment of birth there, daylight saving included. Omit it only to keep the stored one; changing it is free. If the call fails with birth_time_needs_confirming, the clocks changed over that time at the birthplace: ask the user which it was and call again with birthTimeFold (0 = the earlier, 1 = the later). Returns the element profile.
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  • Ask the MU manufacturing router how a thing could be MADE before you create a product: which supplier(s) can make it, the est. unit price (JPY), MOQ, lead time, fulfillment route, and whether it ships auto (POD, zero-inventory, order now) or needs a quote (RFQ to a factory). Pass `kind` (a known POD kind like tee/hoodie/rashguard_ls, OR a non-POD kind like `gi`/`loopwheel_sweat`/`seamless_knit`/`rashguard_premium`) OR a free-text `description` (e.g. "道着 for a dojo", "a seamless knit sweater") and the router infers the kind. Optional `qty`, `region` (e.g. jp/us), `budget` (JPY/unit). Read-only — creates nothing. No API key required. Options are ranked: buyable-now (auto + in budget) first. If an option's mode is `auto`, follow up with mu_create_product; if `quote`, it needs a human RFQ.
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  • How has this on-chain metric moved over time? Returns the full TIME SERIES of one on-chain metric from the Bitcoin Research Kit — date/value pairs in ascending order, with history back to 2009 for most series. Use it for trend and percentile work; for the single current reading call arena_get_onchain_latest, and to discover valid series_ids call arena_list_onchain_series. Values are as-reported: on-chain metrics can be revised retroactively, so this is not a point-in-time vintage. Range capped by tier — the response carries a `range` block (requested_days, granted_days, clamped, clamp_reason, tier), so a clamped window announces itself instead of silently looking like the full history. [Free 30d / Pro 365d / Power unlimited]
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  • Ask a real human to verify, decide on, or improve something before your agent acts. Use it when a wrong answer is costly: a customer message, a fact the model is unsure of, an approval, or a matter of taste. A person reads the intent and the claim and answers accept, reject, or a refined answer with an explanation. This call is gate 1: it costs 0.10 EUR (paid on Base via x402) and returns a payment requirement first if unpaid; reading that requirement is free and shows every later price. intent: what your agent is trying to do (max 2000 chars). claim: the claim a human should verify (max 4000 chars). agent_id: your wallet address (0x + 40 hex). Signs the x402 payments. callback_url: optional HTTPS endpoint for verify.ready or verify.failed. Use it to avoid an active polling loop; retain verify_id for recovery. payment_signature: optional manual compatibility input. Standard x402-aware MCP clients send the signed payment through request metadata automatically. Returns status "processing" with a verify_id. Prefer callback_url, or poll get_verify at the returned interval until status is "ready" or "failed". If ready, call unlock_verify. Only one active verify per agent_id at a time.
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  • Real-time forex quotes: the most-traded pairs, each with a display name. The feed carries 1,550 pairs in alphabetical order, which is far more than one response can hold — so this returns the most prominent `limit` of them (majors first, then by volume), and the response states how many were left out. Pass `symbols` for specific pairs, or call get_forex_quote for a single one. Read `note` before summarising: it says how many pairs the slice covers out of how many exist, so a "top pairs" answer is not mistaken for the whole market. `volume` on a forex row is a per-venue tick count, not market turnover — FX is over-the-counter and most pairs report 0. It does not rank the market. Args: symbols: Comma-separated pairs (optional; overrides the ranked slice) limit: How many ranked pairs to return (optional)
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  • Wind, sea, and where it matters current and tide, at one point. For the questions about a place rather than a passage: how hard it blows at Groix this afternoon, when the thermal breeze fills in, when the mistral eases, whether the models agree, what the swell does at a harbour entrance tonight. Args: lat: latitude in degrees. lon: longitude in degrees. start: ISO-8601 datetime with the user's UTC offset (e.g. "2026-05-01T08:00:00+02:00"). Every time in the answer comes back in that offset. end: ISO-8601 datetime, timezone-aware. models: optional list of model names. Leave it unset for the automatic choice: AROME (1.3 km) wherever it reaches the window, and the next model that reaches its end when the window runs past two days. Name several models (``["arome", "icon_eu", "ecmwf", "gfs"]``) only when the user asks whether the models agree: each one costs a request. Returns hourly ``wind`` per model (speed, direction it comes from, gusts, in knots), ``sea`` (wave height, period, direction), and, only where they are material, ``current`` (speed in knots, direction it flows to, from a tidal atlas where one covers the point) and ``tide`` (height around mean sea level: read the range and the times of high and low water from it, not a depth over chart datum). Each series is a table: ``columns`` names the fields once, each of ``rows`` is one hour. Also ``openwind_url``, the OhMyWind map centred on the point. No widget comes with this tool. The values are a model forecast, not a measurement of what is blowing right now. Pass a point at sea. Open-Meteo Marine answers from the nearest sea cell: a few kilometres inland the ``sea`` values are the open coast's (Guipavas, inland of Brest, gets the waves of the rade), further inland they come back null, the ``sea`` array present and empty of information rather than absent. Wind is always the point's own. Note: the first request after inactivity may incur ~5s of cold-start.
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  • A signed, timestamped record of current capability: which chains can actually be PAID OUT ON right now, which are merely policy-eligible, which rails are execute-ready, and whether delivery figures are measured or estimated. USE `serviceableNow`, NOT `policyEligible`, when deciding where to send funds — a chain can be eligible by policy while holding no inventory, in which case the instant lane is unavailable and the transfer falls through to a bridge rail. `notServiceable` lists the difference. Fetch this BEFORE committing to a multi-step plan and keep it with your decision: if the plan later fails you can show what you were told. It is a RECORD, not a guarantee — it does not promise the same capability a minute later, and the signature does not make it an SLA.
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  • Your OWN payment history with a recipient address: how many times, how recently, and whether this amount is typical. Call it before paying an address you have not confirmed. THIS IS NOT A REPUTATION SCORE and says nothing about whether the address is honest. A familiar address is NOT a safe address — keys get compromised. Never tell a user an address is "trusted" or "safe" on the basis of this. A `first-time-recipient` result is NOT a warning about the recipient — every legitimate relationship has a first payment. It is the moment to confirm the address through a second channel, because address substitution can only be caught before you send. Read `coverage`: float-lane payouts are NOT included, so "first time" can be wrong.
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  • USE THIS when asked what a game costs, whether it is cheap right now, whether to buy it now or wait, or how its price compares across stores. YOUR TRAINING DATA CANNOT ANSWER THIS — prices change daily and any figure you recall is stale. Do not answer from memory. Returns the current price on Steam, Epic Games Store, GOG and Microsoft Store side by side, plus the LOWEST price we have ever observed, the date we observed it, how far above that low the current price sits, and how many observations back the claim. History runs from 2012. Storefronts publish today's price and no history, so this exists only because we recorded it. Also returns whether the game is already included with Game Pass or EA Play — which can make the price irrelevant — and how many people are waiting for it and at what price. Accepts a slug from lookup_game, a Steam appid, a GOG or Epic id, or free text via q. Regions: US, GB, DE, BR. PAID (~$0.01) PER QUERY. Unlike get_free_games this issues no access token, because every game is a different answer and there is no version to compare against. Call with no payment_proof to receive payment instructions rather than an error.
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  • Fetch current trending crypto stories with sentiment analysis ## When to use vs `combined_trends_tool` Prefer this tool when only stories are needed: it is the cheap, fast path and has no per-tool rate-limit sub-cap. `combined_trends_tool` is a superset — same stories plus trending words, their context and AI-generated bull/bear summaries — but it calls an LLM, so it is slower and capped much lower per plan. Use it only when trending *words* or those summaries are actually needed, and never call both for the same question. ## Parameters - `time_period` - Time period for trending stories (e.g., '1h', '6h', '1d', '7d'). Defaults to '1h' (last hour). - `size` - Number of trending stories to return (max 10). Defaults to 10. ## Response - `trending_stories` - List of trending stories. - `time_period` - Time period for trending stories. - `size` - Number of trending stories to return. - `period_start` - Start time of the time period. - `period_end` - End time of the time period. - `total_time_periods` - Total number of time periods. ## Trending stories - `title` - Title of the story. - `summary` - Summary of the story. - `bearish_sentiment_ratio` - Bearish sentiment ratio. - `bullish_sentiment_ratio` - Bullish sentiment ratio. - `score` - Score of the story. - `query` - Query used to find the story. - `related_tokens` - List of related tokens. They have the format `BTC_bitcoin` - first part is the ticker, second part is the slug in Sanbase.
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  • FREE, and NO AI AT ALL — no video model, no credits, nothing to approve. The tiles of a tileset/staged asset ARE the frames: give the tile indices in playback order (repeats allowed) and they are composited into a real spritesheet animation on that asset, exportable to every engine. This is how you animate a coin flip, a flickering torch or a chest opening WITHOUT paying for image-to-video. Try this before animate_asset whenever the motion already exists across the tiles. Returns a jobId — poll get_job.
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