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197,998 tools. Last updated 2026-06-13 03:02

"Creating a Weather Forecast System" matching MCP tools:

  • Create a B2 cloud-backed snapshot (zero local disk, async). Streams container data directly to Backblaze B2 via restic. No local disk impact — billed separately at cost+5%. Runs in background — returns immediately with status "creating". Poll list_snapshots() to check when status becomes "completed". Only available for VPS plans. Requires: API key with write scope. Args: slug: Site identifier description: Optional description (max 200 chars) Returns: {"id": "uuid", "name": "...", "status": "creating", "storage_type": "b2", "message": "B2 cloud snapshot started. Poll list_snapshots()..."} Errors: VALIDATION_ERROR: Not a VPS plan or max snapshots reached
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  • NO AUTH / PUBLIC / READ-ONLY. Builds and validates a copy-pasteable authenticated /api/v2/{dataset}/timeseries HTTP request without sending it. This tool does not execute the request, query weather values, or return forecast data. Use gribstream_query_timeseries when the user asks for actual weather values or CSV/JSON/NDJSON data. Generated direct API requests include Accept-Encoding: gzip, and generated curl commands use --compressed so large responses can be transferred compressed when the client supports it. Do not include request.asOf unless the user explicitly wants backtesting, time travel, or a historical model-run cutoff. The request body must use exact selectors discovered from the catalog or shared-parameter tools, with coordinates in request.coordinates and selectors in request.variables.
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  • Get the latest narrative forecast product from a Weather Forecast Office (WFO). The default product is AFD (Area Forecast Discussion), which explains the meteorological reasoning behind the forecast — synoptic setup, model guidance, and forecaster confidence. Other types: HWO (Hazardous Weather Outlook, 1-7 day severe/flood/winter outlook), ZFP (Zone Forecast Product, zone-by-zone text), SPS (Special Weather Statement, short-fuse advisory). The office code is the 3-letter WFO identifier returned as the "office" field by nws_get_forecast. Fetches the two-hop products API: list endpoint first (newest product), then the full product detail.
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  • Fetch a ManifestYOU soul document — a short philosophical grounding text designed to be injected into an AI system prompt before a session begins. Call this at the start of a session to orient the model toward stillness, precision, or creative expansion before work. Paste the returned soul_document into your system prompt or before the first user message.
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  • Current space-weather snapshot: NOAA R/S/G storm scales (today + 3-day forecast), latest Kp index with its G-scale equivalent and aurora-visibility latitude, and a plain-language status summary. The quickest way to answer "is anything happening right now?" — use before deciding whether to drill into solar wind (noaa_spaceweather_get_solar_wind), aurora (noaa_spaceweather_get_aurora_forecast), or alert details (noaa_spaceweather_get_alerts).
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  • Get daily weather for a location — works for BOTH historical weather (past dates) and forecast (future or no dates). Use this for HISTORICAL weather and "weather on a past date" questions, e.g. "what was the weather in Paris on 2023-07-04" (location: "Paris", start_date: "2023-07-04"). Pass start_date alone for a single day, or start_date + end_date for a range (weather timeline). Returns per-day temp/min/max, humidity, precipitation, wind, and conditions. Example: weather_timeline({ location: "London", start_date: "2024-01-01", end_date: "2024-01-07" }).
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  • Real-time weather conditions and multi-day forecasts via Open-Meteo — free, no API key required

  • Pirate Weather forecast API (Dark Sky-compatible). Free key required.

  • List all personal AI tags. AI tags are automatic message filters: the system runs a lightweight classifier on every incoming message and applies matching tags to threads. This lets AI agents skip expensive full analysis on most messages — they only act on threads that match relevant tags, dramatically cutting LLM costs. When to use: - Check which auto-classification filters exist before creating one - Get tag IDs for add_to_thread / remove_from_thread - See how many threads each tag currently matches Returns all tags with thread counts (non-archived, included threads only).
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  • NO AUTH / PUBLIC / READ-ONLY. Builds and validates a copy-pasteable authenticated /api/v2/{dataset}/runs HTTP request without sending it. This tool does not execute the request, query weather values, or return forecast data. Use gribstream_query_runs when the user asks for actual model-run forecast data or CSV/JSON/NDJSON data. Generated direct API requests include Accept-Encoding: gzip, and generated curl commands use --compressed so large responses can be transferred compressed when the client supports it. The request body must use exact selectors discovered from the catalog or shared-parameter tools, with coordinates in request.coordinates and selectors in request.variables.
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  • Return step-by-step instructions for creating a Kamy API key in the dashboard. Does not open the browser.
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  • NO AUTH / PUBLIC / READ-ONLY. Validates the basic shape, exact selector tuples, and expression syntax of a proposed GribStream /timeseries or /runs request without sending it. This tool does not execute the request, query weather values, or return forecast data. Use this before returning any hand-edited curl or when changing a request from one dataset to another.
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  • Get camping-specific 7-day weather forecast with suitability ratings and gear recommendations. Uses the Open-Meteo API (no key required) to provide: - Daily high/low temps, conditions, precipitation, wind - Camping suitability rating per day (excellent/good/fair/poor/not_recommended) - Gear recommendations based on conditions - Safety warnings for extreme weather - Best camping days in the forecast period Args: latitude: Campground latitude longitude: Campground longitude campground_name: Campground name for context (optional) check_in_date: Planned check-in date ISO format (optional) check_out_date: Planned check-out date ISO format (optional)
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  • Physical climate intelligence for insurance underwriting, agritech, logistics, energy trading and ESG/climate risk disclosure. Three modes: (1) forecast — 14-day daily weather forecast with temperature, precipitation, wind and humidity; (2) historical — daily records and monthly aggregates for any date range since 1940, with anomaly detection (P90/P95 heat events, extreme precipitation days); (3) climate_risk — long-term physical risk scoring combining CMIP6 ensemble projections (2020-2050), altitude, FEMA flood zones (US) and historical baselines. Risk dimensions: flood, heat (days >35°C/year), drought (SPI), wildfire, sea-level. Overall score 0-100 (100 = severe). Location: city string or lat/lon coordinates. Sources: Open-Meteo (keyless, global, 1940→2050), Open-Elevation, FEMA NFHL (US), NOAA CDO (optional NOAA_API_KEY env var for US+global station data). SLA: ≤25s p95. Cache: 1h forecast / 24h historical / 7d climate_risk.
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  • Get the text forecast for a public NWS forecast zone. Returns named forecast periods (e.g., "Today", "Tonight", "Monday") with detailed narrative text — the human-readable, zone-level forecast written by local forecasters. Completes the alert-to-forecast chain: nws_search_alerts returns zone codes in "affectedZones", and nws_find_stations returns them in the "forecastZone" column; use those codes here. Zone codes follow the pattern XXZ### (e.g., "WAZ315" for Western Washington lowlands). County zone codes (XXC###) are not supported — use the forecast zone code.
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  • Get pre-built template schemas for common use cases. ⭐ USE THIS FIRST when creating a new project! Templates show the CORRECT schema format with: proper FLAT structure (no 'fields' nesting), every field has a 'type' property, foreign key relationships configured correctly, best practices for field naming and types. Available templates: E-commerce (products, orders, customers), Team collaboration (projects, tasks, users), General purpose templates. You can use these templates directly with create_project or modify them for your needs. TIP: Study these templates to understand the correct schema format before creating custom schemas.
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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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  • Physical climate intelligence for insurance underwriting, agritech, logistics, energy trading and ESG/climate risk disclosure. Three modes: (1) forecast — 14-day daily weather forecast with temperature, precipitation, wind and humidity; (2) historical — daily records and monthly aggregates for any date range since 1940, with anomaly detection (P90/P95 heat events, extreme precipitation days); (3) climate_risk — long-term physical risk scoring combining CMIP6 ensemble projections (2020-2050), altitude, FEMA flood zones (US) and historical baselines. Risk dimensions: flood, heat (days >35°C/year), drought (SPI), wildfire, sea-level. Overall score 0-100 (100 = severe). Location: city string or lat/lon coordinates. Sources: Open-Meteo (keyless, global, 1940→2050), Open-Elevation, FEMA NFHL (US), NOAA CDO (optional NOAA_API_KEY env var for US+global station data). SLA: ≤25s p95. Cache: 1h forecast / 24h historical / 7d climate_risk.
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  • List all personal AI tags. AI tags are automatic message filters: the system runs a lightweight classifier on every incoming message and applies matching tags to threads. This lets AI agents skip expensive full analysis on most messages — they only act on threads that match relevant tags, dramatically cutting LLM costs. When to use: - Check which auto-classification filters exist before creating one - Get tag IDs for add_to_thread / remove_from_thread - See how many threads each tag currently matches Returns all tags with thread counts (non-archived, included threads only).
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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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  • Multi-day weather forecast (up to 16 days) for a city or lat/lon — daily high/low, precipitation, wind, conditions. Use for "what's the weather this week / will it rain". Args: city: city name (geocoded). lat/lon: alternative. days: 1-16 (default 7).
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  • Get a daily or hourly weather forecast for a location. Returns a list of forecast periods with conditions, temperatures, precipitation probability, and wind. Location can be "lat,lon" coordinates or a city name. Example: forecast({ location: "london", timestep: "1d", units: "metric" })
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