Globalpulse-MCP

Open-Meteo — 7-Day Weather Forecast

globalpulse_weather_get_forecast

Read-onlyIdempotent

Retrieve 7-day daily weather forecasts for any global location. Provide latitude, longitude, and optional timezone; get results in JSON or markdown format.

Instructions

7-day daily weather forecast for any location. No API key, no rate limit. Args: latitude, longitude, timezone (IANA e.g. "Asia/Kolkata"), response_format Examples: Mumbai → lat=19.076, lon=72.877, tz="Asia/Kolkata" | London → lat=51.507, lon=-0.127, tz="Europe/London"

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": {
      "latitude": "<latitude>",
      "longitude": "<longitude>"
    },
    "name": "globalpulse_weather_get_forecast"
  }
}

Input Schema

Name	Required	Default
`latitude`	Yes
`timezone`	No	UTC
`longitude`	Yes
`response_format`	No	markdown

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 28, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already indicate this is a safe, read-only, idempotent operation. The description adds value by stating there are no API key or rate limit constraints, which is useful behavioral context beyond what annotations provide.

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 extremely concise with two clear sentences and a line for arguments and examples. No filler, every sentence is informative.

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

Completeness3/5

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

While the description covers purpose and parameters, it does not describe the return format or what data the forecast contains (e.g., temperature, precipitation). No output schema exists, so this gap affects completeness for an agent.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It lists all parameters with clarifications: latitude, longitude, timezone (with IANA example), and response_format. Examples for Mumbai and London add concrete meaning to values.

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 clearly states the tool provides a 7-day daily weather forecast for any location, which is a specific verb+resource. It distinguishes from sibling tools like historical weather by specifying 'forecast' and '7-day'.

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?

The description notes 'No API key, no rate limit,' implying ease of use and suggesting it's the go-to for quick forecasts. However, it does not explicitly state when not to use or compare to alternatives, but examples provide practical guidance.

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

Deploy Server