Globalpulse-MCP

Open-Meteo — Historical Climate (ERA5, back to 1940)

globalpulse_weather_get_historical

Read-onlyIdempotent

Retrieve historical daily climate data for any location from 1940 to present using ERA5 reanalysis. No API key required.

Instructions

Historical daily climate data for any location, back to 1940 using ERA5 reanalysis. No API key. Args: latitude, longitude, start_date (YYYY-MM-DD), end_date (YYYY-MM-DD), timezone, response_format

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>",
      "start_date": "<start_date>",
      "end_date": "<end_date>"
    },
    "name": "globalpulse_weather_get_historical"
  }
}

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 28, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already provide readOnlyHint, idempotentHint, openWorldHint. Description adds 'No API key' and data source (ERA5), which are useful but not comprehensive. No mention of rate limits, response size, or behavior on invalid coordinates.

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?

Description is two sentences plus an args list, no redundancy. Purpose is front-loaded, and each sentence adds value. No wasted words.

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 six parameters and no output schema, description lacks details on what climate variables are returned, data units, or response structure. It fails to fully prepare the agent for interpreting the output, especially given the complexity of historical climate data.

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 0%, so description must compensate. Description lists all six parameters and gives date format hint (YYYY-MM-DD), but does not explain latitude/longitude bounds, timezone effect, or response_format options beyond naming them.

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?

Description clearly states it provides historical daily climate data back to 1940 using ERA5 reanalysis, and explicitly says no API key. The verb 'get' is implied but the title and description distinguish from sibling 'get_forecast' by specifying historical range.

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?

Description implies use for historical data via 'Historical' and 'back to 1940', but does not explicitly exclude the forecast sibling tool. It lists required arguments, providing clear context for invocation.

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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