weather-intel-mcp

Weather Current

weather_current

Read-onlyIdempotent

Fetch current observed conditions for a US latitude/longitude from the nearest NWS station, returning temperature, humidity, wind, and a text description.

Instructions

Get the latest observed weather conditions for a US location by latitude/longitude, from the nearest NWS observation station: temperature, humidity, wind, and text description.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`lat`	Yes	Latitude in decimal degrees, e.g. 36.1867. US coverage only (National Weather Service).
`lon`	Yes	Longitude in decimal degrees, negative in the western hemisphere, e.g. -94.1288.

Output Schema

TableJSON Schema

Name	Required	Description
`wind`	No
`source`	No
`station`	No
`humidity`	No
`location`	No
`observed`	No
`provenance`	No	Where this answer came from. served_at is when Datakoot answered (UTC); upstream lists the official sources consulted. Datakoot may serve a briefly cached copy, so the source's own observation can be older than served_at.
`description`	No
`temperature`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Oct 15, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive, so safety is covered. The description adds genuinely new behavioral context: results come from the nearest NWS station and coverage is US-only, which explains non-obvious data-sourcing behavior not captured in annotations.

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?

A single front-loaded sentence with no filler: the action, the source, the input method, and the returned fields all appear in one pass. Every clause earns its place.

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?

An output schema exists so return values needn't be enumerated, and the critical US-coverage constraint is stated. What is missing is how out-of-coverage or ocean coordinates are handled (error vs. nearest fallback), a small gap for an otherwise simple read tool.

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% and both lat/lon already carry format examples and hemisphere guidance, so the schema does the heavy lifting. The description only reinforces the lat/lon input pattern and US-only constraint, adding minimal meaning beyond the structured data. Baseline 3 applies.

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 (get) and resource (latest observed weather conditions) plus the scope (US, by lat/lon) and the data source (nearest NWS observation station). This clearly separates it from weather_forecast and weather_alerts without needing to open either schema.

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?

"Latest observed" and "nearest NWS observation station" frame the usage context well enough to distinguish current conditions from forecast twins, but the description never explicitly names weather_forecast as the alternative or states a when-not condition. Clear context, no explicit exclusions.

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

Deploy Server