noaa-tidesandcurrents-mcp

Get Relative Sea Level Trends

noaa_get_sea_level_trends

Read-onlyIdempotent

Retrieve long-term relative sea level trends for a NOAA station or list stations by network; includes trend, error, observation period, and seasonal amplitude for local sea level assessment.

Instructions

Get the long-term relative sea level trend at a NOAA station: trend and error (reported by NOAA in mm/yr or inches/decade — the payload's trendUnits field says which), the observation period (startDate/endDate), and seasonal amplitude.

Relative sea level combines ocean rise AND local land movement (subsidence/uplift), so trends vary widely by station (e.g. strongly positive on the Gulf Coast, negative in Alaska). Requires a station with a long water-level record; omit station to list all (affil "US" or "Global" filters the network).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`affil`	No	Network filter when listing multiple stations.
`station`	No	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.
`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

A4.4/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, open-world behavior, so the description earns credit for adding domain context the annotations cannot: relative sea level conflates ocean rise with local subsidence/uplift, so sign and magnitude vary by station (Gulf Coast positive, Alaska negative), and a long record is required. The trendUnits field disclosure also pre-empts a real ambiguity.

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?

Two tight paragraphs, front-loaded with the primary output (trend and error) before the domain caveat and the listing-mode note. Dense but every clause carries information; only the parenthetical unit aside is mildly redundant with the payload field it names.

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?

An output schema exists, so return-value enumeration is unnecessary, and the description still flags the trendUnits ambiguity an agent would otherwise misread. With annotations covering safety and schema covering parameters, an agent has everything needed to call this correctly in either single-station or list mode.

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 the baseline is 3, but the description adds genuine semantics: omitting station switches the call into list-all mode, and affil then filters that network by US/Global. That is behavior beyond the schema's field-level descriptions.

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 and resource ('long-term relative sea level trend at a NOAA station') and enumerates exactly what comes back: trend value, error, observation period, seasonal amplitude. This clearly separates it from siblings like noaa_get_sea_level_rise_projections (future projections) and noaa_get_water_levels (instantaneous readings).

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

Usage Guidelines4/5

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

Gives clear context: 'Requires a station with a long water-level record; omit station to list all,' and explains the affil filter's role. It stops short of naming alternatives (e.g. projections vs. trends) or stating exclusions, so it is a strong 4 rather than a 5.

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