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lzinga

US Government Open Data MCP

by lzinga

noaa_climate_data

Read-onlyIdempotent

Retrieve NOAA climate observations for temperature, precipitation, snow, and wind by dataset ID and date range, with optional station or location filters.

Instructions

Get climate observations (temperature, precipitation, snow, wind) from NOAA. Requires dataset ID + date range. Optionally filter by station or location.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax observations (default 1000)
end_dateYesEnd date YYYY-MM-DD
dataset_idYesDataset: GHCND=daily, GSOM=monthly, GSOY=annual
start_dateYesStart date YYYY-MM-DD
station_idNoStation ID, e.g. 'GHCND:USW00094728' (Central Park, NYC)
datatype_idNoData type: TMAX, TMIN, TAVG, PRCP, SNOW, SNWD, AWND
location_idNoLocation ID, e.g. 'FIPS:36' (NY state)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2026.9.14
    • addedInput schema / properties / limit / default
      Added value: +1000
  2. Changed1 schema field changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observedv2026.3.9

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds that it returns observations and mentions filter options, which is useful but does not disclose potential pagination limits or rate constraints. Given the annotations, this is adequate but not rich.

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

Conciseness5/5

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

Two concise sentences with zero redundancy. The purpose is front-loaded and the optional filters are stated efficiently.

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

Completeness4/5

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

No output schema exists, but the description states it returns observations and lists the data types. The required parameters and optional filters are clear. Minor gaps like pagination behavior are not critical given the read-only nature and schema coverage.

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

Parameters3/5

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

Schema description coverage is 100%, so parameters are already documented. The description reinforces the required dataset ID and date range but adds no additional syntax or format details beyond the schema. Baseline 3 applies since the schema handles parameter semantics.

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?

Description clearly states the tool retrieves climate observations (temperature, precipitation, snow, wind) from NOAA, distinguishing it from sibling tools like noaa_stations, noaa_locations, and noaa_datasets. The verb 'Get' and specific resource are explicit.

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?

Description specifies required inputs (dataset ID + date range) and optional filters (station/location), giving clear context for invocation. It does not explicitly mention alternatives like noaa_stations for finding station IDs, but the usage is straightforward and self-contained.

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

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