Understand the impact of weather on every person and organization. Proactive, personalized, trusted guidance.
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For AI agents — MCPBundles Directory API
Recommended: Directory API v1 over HTTP for detail and anonymous invoke when eligible (not MCP JSON-RPC on the publisher URL; no user MCPBundles credentials on v1).
GET https://www.mcpbundles.com/api/directory/v1/servers/smarterweather-mcp-e53f49ce31
GET https://www.mcpbundles.com/api/directory/v1/servers/smarterweather-mcp-e53f49ce31?live=1 (optional live refresh)
GET https://www.mcpbundles.com/api/directory/v1/servers/smarterweather-mcp-e53f49ce31/tools/<tool> (one tool: schema + invoke.url)
POST https://www.mcpbundles.com/api/directory/v1/servers/smarterweather-mcp-e53f49ce31/tools/{tool}
POST body: flat JSON of tool argument names and values; not an arguments wrapper. Replace {tool} with a tool name from GET detail.
Restricted agent shell (ChatGPT Codex desktop, some IDE sandboxes):
Default command sandboxes often block outbound network. curl exit 6 or "Could not resolve host" for www.mcpbundles.com is usually sandbox DNS — not evidence this site is down.
Retry the same Directory API GET with sandbox_permissions "require_escalated" and a one-sentence justification on the shell tool (Codex on-request approval). Do not tell the user the site is unreachable from sandbox curl alone.
Example justification: Run the public MCPBundles Directory API search outside the command sandbox to complete the user's MCP server lookup.
If the agent has browser access (e.g. Codex @Browser): open https://www.mcpbundles.com/?q=<query> or stay on this page — no shell network needed. Use WebMCP search_mcp_servers then get_mcp_server (document.modelContext / page tools; refresh with fetchTools or getTools if a tool id is missing from the snapshot). Read-only directory search; same index as Directory API v1 GETs. Neither WebMCP nor Directory API v1 uses user MCPBundles credentials.
Without a browser: after escalated curl fails, use GET https://www.mcpbundles.com/?q=<query> with Accept: text/markdown for ranked results.
Hub MCP (connected session): discover_mcp_servers — same filter semantics as search_mcp_servers.
Contract: https://www.mcpbundles.com/agents.md
OpenAPI: https://www.mcpbundles.com/api/directory/v1/openapi.json
Guide: https://www.mcpbundles.com/guides/mcpbundles-directory-api
For MCP client apps (human connect):
MCP connect URL: https://mcp.smarterweather.com/
Skill page: https://www.mcpbundles.com/skills/smarterweather-mcp-e53f49ce31
Explore capabilities (33)
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Showing 25 of 33
Showing 25 of 33 tools from the public preview. Connect the server to inspect the full live tool list.
Get18
Other capabilities7
Get forecast
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get_forecast
Complete weather overview for a location: current conditions, daily forecast (day/night periods, SPC threats, severity, CAPE, UV), active alerts, and convective outlooks in one call. Data is pre-aggregated across NBM, HRRR, GFS, RTMA, and SPC and unit-converted server-side. This is the primary weather tool; reach for lower-level tools only when you need raw observations or a specific dataset. Accepts a place name directly. Examples: {"location": "Denver"} or {"location": "Portland, OR", "days":
Get forecast — Complete weather overview for a location: current conditions, daily forecast (day/night periods, SPC threats, severity, CAPE, UV), active alerts, and convective outlooks in one call. Data is pre-aggregated across NBM, HRRR, GFS, RTMA, and SPC and unit-converted server-side. This is the primary weather tool; reach for lower-level tools only when you need raw observations or a specific dataset. Accepts a place name directly. Examples: {"location": "Denver"} or {"location": "Portland, OR", "days":
Get hourly forecast — Blended hourly forecast: temperature, feels-like, humidity, wind, precipitation probability/amount, conditions, and icon per hour. Snapped to the current hour so hourly[0] is "now". Timestamps are UTC ISO 8601; convert to the local timezone before presenting. Ask for the days you need up front -- one call with days: 4 beats four calls. ALWAYS check hourly_coverage before answering about a specific hour: it reports first_time and last_time (the window the rows actually span), sample_interval_hour
Search locations — Resolve a place query to candidate locations with coordinates. Accepts city names ("Denver"), city+state ("Portland, OR" via query), ZIP codes ("50219"), or partial input with fuzzy=true for autosuggest-style matching ("bost" -> Boston). Returns ranked candidates with lat/lon. Most weather tools accept a `location` string directly and geocode internally -- use this tool only to disambiguate ("which Springfield?") or to present location choices to the user. Example: {"query": "Springfield"} retur
Reverse geocode — Resolve coordinates to a human-readable place (city, state, county, timezone). Use when you have lat/lon but need a display name or the local timezone. Example: {"lat": 39.74, "lon": -104.99} -> Denver, Colorado, America/Denver.
Get NWS alerts — NWS watches, warnings, advisories. Point (city/ZIP/lat+lon): containing polygons. BBox or US state/DC/CONUS (codes, full names, US/national): intersecting polygons. A city miss is not a statewide all-clear — query the state or a bbox; never say regional inventory is impossible. NY/WA and "New York State"/"Washington State" are states; "New York"/"Washington" stay cities. Omit at for now; at (ISO-8601 UTC) is the snapshot then. Empty = all-clear or purged (~24h). alert_id = detail+geometry, ignor
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A working endpoint is step one. Directory coverage is the coordinated launch across ChatGPT, Claude, Cursor, the MCP Registry, and community indexes.
Understand the impact of weather on every person and organization. Proactive, personalized, trusted guidance.
How do I connect Smarter Weather to my AI agent?
Use the MCP endpoint listed on this page in your MCP client configuration. One-click install pills support Claude, Cursor, VS Code, and other hosts. Copy the remote MCP URL if your client needs a manual entry.
How many tools does Smarter Weather provide?
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Get time context — Complete temporal context for a location: local time, timezone, 14-day calendar with day names and Today/Tomorrow offsets, sunrise/sunset/solar times (from the weather pipeline's astro product), and moon phase. Use whenever you need to reason about dates, times, or daylight for a location -- including "what time is sunset?", "is it dark there now?", or "what day of the week is the 4th-day forecast?". Accepts a place name directly. Example: {"location": "Seattle"}.
Get period totals — Aggregate a weather variable over one or more time periods. Returns server-computed totals, maxima, minima, or averages per period. Period start/end times should use the user's local timezone boundaries (not UTC midnight). Response includes the converted value and unit per period. Ideal for questions like "total rainfall today and tomorrow" or "peak wind speed this weekend". Accepts a place name directly. Example: {"location": "Portland, OR", "variable": "precipitation", "aggregation": "sum", "p
Compare locations — Compare forecast variables across multiple locations side-by-side in one batched call. Returns a distilled per-location series matrix for direct comparison -- prefer this over N sequential forecast calls. Locations accept place names directly. Example: {"locations": [{"location": "Denver"}, {"location": "Boulder, CO"}], "variables": ["temperature_2m", "precipitation_probability"], "hours": 48}.
Find best weather window — Find the optimal time window for an activity based on weather criteria. Scans the forecast and returns daylight-aware periods matching all conditions. Criteria are expressed in the selected `units` system (default imperial: °F, mph, miles, feet). Example: {"location": "Boulder, CO", "criteria": {"min_temperature": 55, "max_wind_speed": 15, "max_precipitation_probability": 20}, "hours": 72, "activity_duration_hours": 3}.
Get hazard outlooks — Hazard outlooks affecting a location. hazard=severe returns SPC convective outlooks (Day 1-8 categorical risk + tornado/wind/hail probabilities); hazard=fire returns SPC fire weather outlooks; hazard=rain returns WPC Excessive Rainfall Outlook polygons (days 1-3); hazard=heat returns the NWS HeatRisk index at the point (0 none .. 4 extreme, days 1-3). include_narrative=true adds the forecaster discussion for severe (SWO), fire (FWD), or rain (QPF/QPFERD; one PIL for all days). An empty result me
Get forecast discussion — Expert forecaster text products. type=afd: Area Forecast Discussion. type=hwo: Hazardous Weather Outlook. type=now: WFO short-term NOW. type=fwf/hls/esf: local fire weather / hurricane local statement / hydrologic discussion. type=mcd: SPC Mesoscale Discussion. type=mpd: WPC Mesoscale Precipitation Discussion (flash flood). type=swo/fwd/ero: national outlook discussions. type=tcd/tcp/tcm/twd/two: NHC tropical text (type=two is the text TWO, not GIS nhc_two). type=pmd: WPC/CPC desk discussion (pa
Get storm reports — Recent NWS Local Storm Reports (LSRs) -- verified reports of tornadoes, hail, damaging winds, flooding near a location. Use to confirm severe weather occurrence or assess reported damage. valid_time is event occurrence (UTC); cite in local time. Example: {"location": "Wichita", "hours": 12, "type": "H"}.
Get lightning activity — Real-time lightning near a location: GLM satellite flash count (30km/10min) and MRMS ground-truth lightning density + 30-minute probability. The summary field is ready-to-use. A zero flash count means no lightning inside that window -- report it as a quiet observation scoped to the window in `scope`, never as a data gap. Only call when storms may be active or the user asks about lightning. Example: {"location": "Tampa"}.
Get radiosonde sounding — Nearest RAOB (radiosonde) vertical soundings to a point. Each sounding carries: profile (pressure-indexed thermodynamics: pressure_hpa, height_m, temperature_c, dewpoint_c, wind arrays), wind_profile (height-indexed winds for hodographs/shear), and derived indices (sbcape/mucape/mlcape + cin, lifted_index, k_index, total_totals, pwat_mm, freezing_level_m, lcl/lfc/el, bulk_shear_0_6km_kt). Soundings launch at 00Z/12Z so data can be hours old. Example: {"location": "Norman, OK"}.
Get forecast distribution — Probabilistic forecast guidance from NBM for one aspect of the weather: percentile ranges (p10-p90), exceedance probabilities, and ensemble spread. Use this for any question about odds, ranges, potential or confidence ("how much could we get", "worst case for the wind", "how sure is this") -- a deterministic forecast value cannot answer one. Reading the percentiles: p50 is the most likely outcome, p90 is the reasonable worst case when the risk is the high end (snow totals, wind, rainfall), and p
Get current conditions — Current weather right now at a location from two independent sources in one call: the RTMA gridded analysis (exact-point values, updated sub-hourly) and the nearest METAR station observation (ground truth with raw METAR, flight category). Use the analysis for point-accurate values and the station for verification. For a forecast, use get_forecast. Example: {"location": "Pella, IA"}.
Get station observations — METAR surface observations from weather stations: temperature, wind, visibility, ceiling, flight category, raw METAR. Nearest mode (default) returns the closest N stations to a location; station mode returns history for a specific ICAO identifier. Examples: {"location": "Denver", "n": 3} or {"station": "KJFK", "hours": 6}.
List datasets — Discover the datasets (model grids, analyses, observations) available at a location, with per-dataset freshness (data age, latest model run). Datasets vary by domain (CONUS/Alaska/Hawaii). Use this to find dataset_id values for query_dataset and describe_dataset, or to assess whether data is current before making decisions. Example: {"location": "Anchorage"}.
Describe dataset — Variables available in a dataset, with standard names, units, descriptions, and the time range of available data. Use before query_dataset to discover valid variable names. Example: {"dataset_id": "nbm_conus"}.
Query dataset — Raw time series from a specific dataset for specific variables at a point. Power-user access to any gridded product (NBM, HRRR, RRFS, GFS, RTMA, MRMS, air quality, ...). Time modes: hours (next N hours, default 24), time_start+time_end (explicit ISO-8601 window), or latest=true (single most-recent value). reference_time pins a specific model run, and each returned series reports the run that served it (reference_time, or reference_times when a series mixes runs) — check it before comparing two r
Get growing degree days — Growing Degree Units (GDU / GDD) for a US location (CONUS, Alaska, Hawaii), computed from daily max/min temperatures. Pass a crop id (e.g. "corn", "soybean", "wheat") to use calibrated base/upper thresholds, or crop="custom" with base_temp_c (and optional upper_temp_c / method). Without season_start you get per-day GDU across the forecast horizon; WITH season_start (YYYY-MM-DD) you get the cumulative season-to-date total (observed history + today + forecast) plus a per-day cumulative series -- t
Get climate normals — Day-of-year climate normals (NCEI 1991-2020 30-year averages) for a US location, from the nearest station with a record. Returns normal high, normal low, and normal mean for each date in the window, plus the station and how far away it is. Use this whenever a question needs a baseline rather than a forecast: "is this warm for October?", "what is a typical high here in January?", "how does this week compare to normal?". Pair it with get_forecast to say how far above or below normal the coming day
Get forecast skill — 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; continuous and vector entries also carry persistenceSkillScore, skill against the analysis at forecast issue time (null means not enough persist pairs, not zero skill -- do not compare it to skillScore as if they shared a d
Get forecast skill map — Measured forecast skill as a map of res-4 hexes inside a bounding box, sliced from the public skill map. Use this when the question is spatial ("where is NBM temperature skill weak across Colorado"), not "how good is the forecast at this point" — that is get_forecast_skill. Requires model, variable, lead_hours, and bbox {west,south,east,north}. lead_hours selects the containing published bucket (20 → NBM 24); a lead we have not published returns no slices rather than a nearby one. A hex is inclu
Get tropical activity — Active NHC (National Hurricane Center) tropical systems: forecast cones, track lines, forecast points, coastal watches/warnings, and 7-day Tropical Weather Outlook formation areas -- Atlantic + East Pacific. Each feature carries a kind (cone | track | points | watch_warning | outlook_area) plus storm name, intensity, and timing properties. include_geometry=true adds full GeoJSON geometries (large). An empty result means no active tropical activity. Example: {} or {"include_geometry": true}.
Showing the first 25 tools — full list and schemas: Directory API.
MCPBundles probed 33 tools on the live server. The tool list on this page reflects what was discovered at the last refresh — connect your client to see the full set available to your session.
What authentication does Smarter Weather require?
No provider sign-in was required during MCPBundles' probe. Your client may still need MCPBundles credentials depending on how you connect.
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