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MCP Weather

get_weather

Retrieve current weather for any city. Uses cached data for major cities and live web search with AI extraction for others.

Instructions

Get the current weather for a city.

Checks a local cache first. On a cache miss performs a live web search via Serper and formats the result with DeepSeek V4 Pro.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses the cache-first behavior, the live web search via Serper on a miss, and the DeepSeek V4 Pro formatting. This is explicit about underlying mechanics and gives the agent a realistic mental model of the call.

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 tightly written sentences: the first states the core purpose, the second reveals the processing pipeline. There is zero filler, and the most important information is front-loaded.

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?

This is a simple one-parameter tool with an output schema present, so return-value explanation is not required. The description covers the cache/search/format pipeline completely. The only notable gap is the ambiguous 'city' parameter format, which slightly reduces completeness.

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?

Schema description coverage is 0% – the schema only defines 'city' as a string with no format constraint. The description merely repeats 'for a city' and does not clarify format (e.g., 'London' vs 'London, UK'), case sensitivity, or acceptable values, so it fails to compensate for the schema's silence.

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?

The description opens with a specific verb and resource: 'Get the current weather for a city.' This unambiguously states what the tool does, and even without sibling tools, the purpose is immediately clear to an agent.

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?

There are no sibling tools, so no alternative-routing guidance is needed. The description provides clear context for when to use the tool (current weather retrieval) and implies an exclusion of forecasts through the word 'current', but it does not explicitly state when not to use it.

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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