noaa-tidesandcurrents-mcp

Get Observed Water Levels

noaa_get_water_levels

Read-onlyIdempotent

Retrieve observed water levels from a NOAA tide station as a time series. Use it for current readings, storm surge analysis, or comparing observed vs predicted tides.

Instructions

Get observed water levels from a NOAA tide station as a time series.

Choose the interval: "6" = standard 6-minute observations (preliminary or verified, max 31 days per request), "1" = 1-minute preliminary data (max 4 days), "hourly" = verified hourly heights (max 1 year). Heights are relative to the requested datum (MLLW by default — the US nautical chart zero).

Returns per record: t (timestamp in requested time zone), v (height), s (sigma), f (quality flags, decoded in output), q (p=preliminary, v=verified). Recent data is preliminary; verification takes days to weeks.

Use for: "what is the water level right now" (date=latest), storm surge analysis, comparing observed vs predicted tide. Do NOT use for future tides — use noaa_get_tide_predictions.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date`	No	Shortcut window: "today" = midnight to now, "latest" = single most recent reading, "recent" = last 72 hours. Mutually exclusive with begin_date/end_date/range.
`datum`	No	Vertical reference datum for heights. MLLW is the standard chart datum for coastal stations. IGLD and LWD apply to Great Lakes stations ONLY; NAVD/CRD exist only at stations where computed. Check a station's supported datums with noaa_get_station_datums.	MLLW
`range`	No	Number of hours. With begin_date: hours forward. With end_date: hours back. Alone: hours back from now.
`units`	No	Unit system. english: feet, °F, knots (wind AND currents), nautical miles. metric: meters, °C, m/s for wind but cm/s for currents, kilometers. Air pressure is millibars and salinity is PSU in BOTH systems.	english
`station`	Yes	Station ID. Water-level/met stations use 7-digit numeric IDs (e.g. "9414290" San Francisco); current stations use alphanumeric IDs (e.g. "cb0102"). Find stations with noaa_search_stations or noaa_find_nearest_stations.
`end_date`	No	End date/time. Same formats as begin_date.
`interval`	No	Observation interval: "6" = 6-minute (standard, 31-day max), "1" = 1-minute preliminary (4-day max), "hourly" = verified hourly heights (1-year max).	6
`time_zone`	No	Time zone for timestamps: gmt = UTC, lst = station local standard time (no DST), lst_ldt = station local time with DST. Note: daily_mean data requires lst.	lst_ldt
`begin_date`	No	Start date/time. Formats: yyyyMMdd, "yyyyMMdd HH:mm", MM/dd/yyyy, or ISO yyyy-MM-dd[THH:mm].
`response_format`	No	Output format: "markdown" for a readable summary table, "json" for the complete structured payload.	markdown

Output Schema

TableJSON Schema

Name	Required	Description	Default
`_response`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.0.1Oct 5, 2026

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuinely new behavioral context: preliminary vs verified data status, the days-to-weeks verification lag, hard window limits per interval, datum semantics, and per-record field decoding (t, v, s, f, q). That is substantive disclosure well beyond the annotation layer.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action, then organized into labeled chunks (intervals, return record, use cases) so a reader can stop early. Slightly long for the payload, with some overlap between the interval paragraph and the interval parameter description, but no filler sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A 10-parameter tool with an output schema present, and the description still covers window limits, datum caveats, freshness caveats, and intended/forbidden uses. Nothing an agent needs to call it correctly is missing, and return-value detail is arguably bonus given the output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds practical selection meaning the schema does not: why to pick '1' vs '6' vs 'hourly', what MLLW means as chart zero, and that recent readings are preliminary. Its interval explanation does partially duplicate the schema's own wording, capping it below 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Get observed water levels from a NOAA tide station as a time series') and immediately distinguishes itself from the prediction siblings by scoping to observed data. An agent can tell it apart from noaa_get_tide_predictions, noaa_get_extreme_water_levels, and noaa_get_top_ten_water_levels without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names use cases ('what is the water level right now' with date=latest, storm surge analysis, observed vs predicted comparison) and an exclusion with a named alternative: 'Do NOT use for future tides — use noaa_get_tide_predictions.' This is the explicit when/when-not/alternative pattern at full strength.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.