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AmplifyAutomation

Weather MCP Server

get_forecast

Retrieve weather forecasts for US locations using latitude and longitude coordinates. Get forecast data from the National Weather Service to plan activities.

Instructions

Get weather forecast for a location.

Args: latitude: Latitude of the location longitude: Longitude of the location

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latitudeYes
longitudeYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

There are no annotations, so the description bears the full burden of behavioral disclosure. It only says 'Get weather forecast' and gives no information about safety (read-only vs. side effects), units, time range, caching, or output structure. Such missing details matter for an external forecast API.

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?

The description is short and purpose-first, with a separate Args block for parameters. It is efficiently structured, though the Args section largely duplicates the input schema and could be trimmed without loss.

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

Completeness2/5

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

With no output schema and no annotations, the description should explain what forecast data is returned (e.g., temperature, precipitation, time horizon), coordinate constraints, and how this relates to the sibling get_alerts. It does none of these, so an agent lacks essential information for correct invocation and interpretation.

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

Parameters2/5

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

The description repeats the parameter names with minimal elaboration ('Latitude of the location'), which adds little beyond the input schema titles 'Latitude' and 'Longitude'. It does not specify units (e.g., decimal degrees), valid ranges, or coordinate format, so the parameter semantics are under-specified.

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

Purpose4/5

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

The description states a clear verb and resource: 'Get weather forecast for a location.' This distinguishes it from the sibling tool get_alerts, which obviously deals with alerts rather than forecasts, even though it does not explicitly name the sibling.

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

Usage Guidelines2/5

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

No guidance is provided about when to use get_forecast versus get_alerts or any other alternative. The description gives no contextual hints about use cases, prerequisites, or exclusions.

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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