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362,178 tools. Last updated 2026-08-01 19:01

"A server for checking weather forecasts" matching MCP tools:

  • Forecast Vintages — third-party forecasts (research firms like TrendForce/WSTS/SEMI, and company capex/bit-growth guidance) archived with their ORIGINAL publication date. Query the REVISION HISTORY, not just the latest number: "what did TrendForce say about 2026 HBM bit growth in January vs July?". Each row: originator, originator_type, metric, target_period (e.g. CY2026, 2027H1), value (num or low/high), unit, as_of (publication date), a source URL, and a verbatim quote. This is the vintage archive of OTHER organizations' forecasts — distinct from our own scenario models. USE THIS for: forecast revision tracking, "how has the 2026 capex outlook moved across TSMC's earnings calls?", comparing what different firms projected for the same target period, building a consensus-vs-time view. DO NOT USE for: current cost/pricing values (use get_wafer_pricing / get_accelerator_costs); our own scenario projections (those live on /market-data/*/forecast). Filters: originator, originator_type (research_firm|company_guidance|government|bank|industry_body|other), metric, target_period, entity_id. Latest slice for all tiers; full history (from/to/since/all) needs a Pro key — free callers get the latest slice with a note, never an error. Cite as "Silicon Analysts — Forecast Vintages".
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  • Retrieves comprehensive weather data including current conditions, hourly, and daily forecasts. **Specific Data Available:** Temperature (Current, Feels Like, Max/Min, Heat Index), Wind (Speed, Gusts, Direction), Celestial Events (Sunrise/Sunset, Moon Phase), Precipitation (Type, Probability, Quantity/QPF), Atmospheric Conditions (UV Index, Humidity, Cloud Cover, Thunderstorm Probability), and Geocoded Location Address. **Location & Location Rules (CRITICAL):** The location for which weather data is requested is specified using the `location` field. This field is a 'oneof' structure, meaning you MUST provide a value for ONLY ONE of the three location sub-fields below to ensure an accurate weather data lookup. 1. Geographic Coordinates (lat_lng) * Use it when you are provided with exact lat/lng coordinates. * Example: {"location": {"lat_lng": {"latitude": 34.0522, "longitude": -118.2437}}} // Los Angeles 2. Place ID (place_id) * An unambiguous string identifier (Google Maps Place ID). * The place_id can be fetched from the search_places tool. * Example: {"location": {"place_id": "ChIJLU7jZClu5kcR4PcOOO6p3I0"}} // Eiffel Tower 3. Address String (address) * A free-form string that requires specificity for geocoding. * City & Region: Always include region/country (e.g., "London, UK", not "London"). * Street Address: Provide the full address (e.g., "1600 Pennsylvania Ave NW, Washington, DC"). * Postal/Zip Codes: MUST be accompanied by a country name (e.g., "90210, USA", NOT "90210"). * Example: {"location": {"address": "1600 Pennsylvania Ave NW, Washington, DC"}} **Usage Modes:** * **Current Weather:** Provide `location` only. Do not specify `date` and `hour`. * **Hourly Forecast:** Provide `location`, `date`, and `hour` (0-23). Use for specific times (e.g., "at 5 PM") or terms like "next few hours" or "later today". If the user specifies minute, round down to the nearest hour. Hourly forecast beyond 120 hours from now is not supported. Historical hourly weather is supported up to 24 hours in the past. * **Daily Forecast:** Provide `location` and `date`. Do not specify `hour`. Use for general day requests (e.g., "weather for tomorrow", "weather on Friday", "weather on 12/25"). If today's date is not in the context, you should clarify it with the user. Daily forecast beyond 10 days including today is not supported. Historical weather is not supported. **Parameter Constraints:** * **Timezones:** All `date` and `hour` inputs must be relative to the **location's local time zone**, not the user's time zone. * **Date Format:** Inputs must be separated into `{year, month, day}` integers. * **Units:** Defaults to `METRIC`. Set `units_system` to `IMPERIAL` for Fahrenheit/Miles if the user implies US standards or explicitly requests it. * The grounded output must be attributed to the source using the information from the `attribution` field when available.
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  • Get Lenny Zeltser's CTI cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `cti_load_context`. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
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  • Return a single recommended VPS provider for users who do not yet have a server. Call this ONLY when the user explicitly says they have no server. The user buys the VPS at this provider and comes back with IP + password.
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  • Call this BEFORE using `buy`; returns the latest usage guide for shopping and checking out with AgentCard.
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Matching MCP Connectors

  • Real-time weather conditions and multi-day forecasts via Open-Meteo — free, no API key required

  • Forecasts, climate history, severe alerts by location — for outdoor-event planners.

  • How accurate our forecasts have actually been near a location, measured against observed analysis truth. Returns bias (positive = the model runs high), mean absolute error, RMSE, and a skill score against local climatology, per model, weather variable, and forecast lead time; for probability forecasts, the Brier score and a reliability breakdown. Use this to qualify a forecast rather than assert it -- "NBM has been running 1.8F warm at 3-day leads near you, so treat that 72 as around 70" -- and to answer "how much should I trust this forecast", "is the model biased here", or "how accurate were you last month". Evidence is reported at three scopes side by side: the exact point (strongest, slowest to accumulate), the ~50km neighborhood, and the ~300km region. Prefer the most specific scope that has samples. Metrics below minimumSamples observations are withheld and listed under insufficientHistory with their count -- say that history is still accumulating rather than treating thin numbers as evidence. Coverage is a rolling recent window over verified US variables, not all of history. Entries are per model and their samples are not matched, so never conclude that one model beats another by comparing their numbers here. Each entry states the truth field it was measured against -- one designated analysis per variable -- so never compare numbers carrying different truth values either.
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  • Get a multi-day weather forecast for any Swiss location. Returns daily summaries (temperature, precipitation, sunshine, wind, weather icon) plus a hierarchical hourly breakdown of every series. This uses official MeteoSwiss Open Data — the same forecasts powering the MeteoSwiss app and website. Accepts: - Postal codes: "8001" (Zurich), "3000" (Bern), "1200" (Geneva) - Station abbreviations: "SMA" (Zurich Fluntern), "BER" (Bern) - Place names: "Zurich", "Basel", "Lugano" Coverage: ~6000 Swiss locations (all postal codes + weather stations + mountain points). Forecast horizon: up to 9 days. Updated hourly. Each day's summary fields: temperature_min_c, temperature_max_c, precipitation_total_mm, sunshine_total_minutes, wind_avg_kmh, wind_gust_max_kmh, weather, weather_icon_url. Each day also includes "hourly": one array of per-hour objects covering every series together — { time, temperature_c, precip_mm, sunshine_minutes, wind_kmh, wind_gust_kmh } — useful for judging *when* rain, sun, or wind is expected, not just the daily summary: - Each entry's "time" is already local wall-clock time for the location (Europe/Zurich), with the UTC offset included, e.g. "2026-07-09T14:00:00+02:00". It is NOT UTC — do not convert it. - A dry/calm/sunless hour is reported as its measured value (often 0), not omitted. A fully dry day is still a full array of zero-precipitation hours, not an empty array. - Each field is independently null if just THAT series has no reading for a given hour — the other fields for that same hour are still populated. An hour is omitted entirely only when every series is missing for it. - "hourly" itself is null when no hourly breakdown exists for this location at all (a total data gap); [] only when this location supports hourly data but none was available for that specific day. - For weather stations, temperature_min_c/temperature_max_c/precipitation_total_mm are MeteoSwiss's own official daily aggregates — a different, separately-curated product from the hourly series shown alongside them. They can legitimately NOT match summing/ averaging the hourly entries for that day; this is expected, not a data error. sunshine_total_minutes/wind_avg_kmh/wind_gust_max_kmh have no official daily product for stations and are always derived from the hourly series. For postal codes/mountain points, every summary field is derived from the same hourly series shown alongside it, so it always matches summing/averaging that series exactly.
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  • Returns real-time AIS positions, speed, heading, ETA, and dock status for all active WSF vessels. Use for "where is the ferry now?", vessel tracking, or checking if a vessel is in service. Position data may lag by 30–60 seconds. Many fields are null for vessels not currently operating.
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  • Use this when you have VaR or Expected-Shortfall forecasts and need to know whether reality breached them more often or deeper than your claimed tail level allows -- a risk-forecast audit, not buy/sell advice. Does your risk model's VaR/ES forecast survive contact with reality? Exceedance backtest over YOUR forecasts -- a new claim type: risk numbers, not return claims. Submit realised per-period returns plus the VaR forecasts your model produced ex ante (positive loss thresholds at tail level alpha, e.g. 0.05 for a 95% VaR), optionally the matching expected-shortfall forecasts. The breach count is graded on the EXACT binomial Basel traffic-light zones (Basel Committee 1996: green below cumulative probability 0.95, yellow to 0.9999, red above) -- published boundaries, no house thresholds; red earns the named demote VAR_BREACH_RATE_EXCESS. Kupiec's proportion-of-failures LR (1995) and Christoffersen's independence LR (1998) ride along -- clustered breaches flag the advisory var_breaches_clustered (a model blind to volatility clustering). If ES forecasts are supplied, a joint (VaR, ES) mixture e-process (e-backtesting, Wang & Ziegel) grades breach DEPTH: crossing Ville's anytime-valid 1% line earns ES_TAIL_UNDERSTATED. Supply benchmark_var_forecasts (and optionally benchmark_es_forecasts, e.g. a rolling historical quantile) and the assay also tests EQUAL PREDICTIVE ABILITY: Diebold-Mariano (1995) on a strictly consistent loss (quantile tick, or the joint FZ0 loss of Fissler & Ziegel 2016 when both sides carry ES) -- a naive benchmark that beats your model past the one-sided 5% line earns RISK_FORECAST_DOMINATED_BY_BENCHMARK; the attention zone to 10% is the advisory risk_forecast_lags_benchmark. Demote-only: too many breaches can kill, too few is the mis-calibration advisory var_breach_rate_sparse -- conservative models pass with a flag, never a blessing. Code-computed end to end, fail-closed on malformed or undersized input (a series too short to reach the red zone answers insufficient_evidence instead of a hollow pass). Works for any asset class. NOT financial advice; no order path. Price: per check; see https://api.alphaassay.com/v1/meta/pricing (api_key required -- account setup at https://api.alphaassay.com/account).
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  • Returns the Smarter Weather developer request-access URL (with MCP referral attribution). The developer platform is in limited preview: signup is invite-based. Present the URL to the user so they can request access in a browser; once they receive and accept an email invitation, they authenticate this MCP server via OAuth to continue onboarding (key minting, client configuration). No authentication required.
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  • Get VoxOdds' audited AI-vs-market forecast track record. Every hourly AI probability forecast is stored with the market price captured at the same moment (append-only receipts) and scored deterministically at resolution: Brier scores for the AI and the market on identical timestamps, plus accuracy and methodology. Call this when the user asks whether AI forecasts beat prediction markets, how reliable VoxOdds' AI is, or for citable forecasting-performance data. Losses are published too — the record is auditable, not curated.
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  • Get a 14-day weather forecast for a campsite or location. Use this when the user asks about weather, temperature, rain, wind, or UV conditions at a campsite or destination. You can provide EITHER: - campsite_name: The name (or partial name) of a campsite to look up its GPS coordinates automatically, OR - latitude + longitude: Direct coordinates if already known Returns daily forecasts with max/min temperature, rain chance, precipitation amount, wind speed, UV index, and a weather description for each day.
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  • Return every detector word/phrase list with its entry count, config key, and sample entries, plus a link to the full browsable library. Read-only, takes no parameters, and returns the same catalog for a given release. Use it to see what the detectors match before tuning a config for check_text; not needed for ordinary checking.
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  • Check whether a handle is available on unu.lu (not other platforms like Instagram, TikTok, etc.). For example, checking 'joe' tells you if joe.unu.lu is available for claiming. Use this to help users choose a handle before they visit the claim page.
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  • Get the curated daily weather-intel brief — the day's most significant weather in one package, from NOAA/NWS and Open-Meteo. Includes active severe NWS weather alerts, significant weather events of the last 24h, a 72-hour forecast outlook for major US metros, and agricultural weather signals (growing-degree-days, frost risk, soil, precipitation). Each brief carries a verifiable provenance attestation so a buyer can verify it was produced by this server, unaltered. PAID: $5 per brief. Defaults to today (UTC); a brief expires at the next midnight UTC. On a 402, pay the returned payment memo and re-call with the SAME args plus payment_tx=<signature>. An Authorization: Bearer fnet_ key bypasses payment.
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  • Get Lenny Zeltser's IR cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `ir_load_context`. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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  • List pending mempool transaction hashes via DERO.GetTxPool. When to call: when checking unconfirmed activity, watching for a specific tx to land, or estimating mempool pressure. NOTE: `tx_hashes` may be `null` or an empty array when the mempool is empty — treat both as "no pending". Input Requirements: none. Output: `{ tx_hashes: string[] | null }`.
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  • Find airports within a radius of a latitude/longitude, ranked nearest-first by great-circle distance, each with its distance (km) and bearing (degrees true) from the query point. The grounding tool for "nearest airport to here" — pair it with a live aviation server to fetch weather or positions for the result. Takes a coordinate only: no geocoding, so resolve place names to lat/lon upstream first (e.g. an OpenStreetMap or Open-Meteo geocode tool). Closed airports are excluded unless include_closed is set. OurAirports is community-edited — not authoritative for flight operations.
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