mcp-pt

weather_forecast

Get a 5-day weather forecast for any Portuguese city or locality using official IPMA data. Simply provide the location name to receive current and upcoming weather conditions.

Instructions

5-day weather forecast for a Portuguese location (data: IPMA). Give a city/locality name.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "location": "<location>"
    },
    "name": "weather_forecast"
  }
}

Input Schema

Name	Required	Description	Default
`location`	Yes	Location name, e.g. 'Lisboa', 'Porto', 'Faro', 'Funchal'

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 19, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses the time range (5-day) and data source (IPMA), but omits critical behavioral traits such as whether the forecast is read-only, what happens on invalid locations, data freshness, rate limits, or response format. The description is too minimal to ensure safe invocation.

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?

The description is a single, front-loaded sentence of 16 words. It conveys the essential information without superfluous text. Every word earns its place.

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?

Given the tool's simplicity (one parameter, no output schema, no annotations), the description is too sparse. It does not explain the return value structure, error handling, or any constraints. An agent would lack enough context to interpret the forecast output or handle edge cases adequately.

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 coverage is 100% for the single parameter 'location', so the baseline is 3. The description adds the phrase 'city/locality name', which slightly reinforces the schema's examples ('Lisboa', 'Porto'). This adds minimal extra meaning beyond the schema's existing description.

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 clearly states the tool provides a '5-day weather forecast for a Portuguese location' and specifies the data source (IPMA). It is a specific verb+resource combination. However, it does not explicitly differentiate from the sibling tool 'weather_warnings', leaving the agent to infer the distinction from the tool names alone.

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?

The description gives a basic instruction ('Give a city/locality name') but provides no guidance on when to use this tool versus alternatives (e.g., weather_warnings for alerts, fuel_prices for unrelated data). It lacks explicit context about when to use or not use this tool.

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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