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cmer81

Open-Meteo MCP Server

by cmer81

ensemble_forecast

Access ensemble weather forecasts to analyze forecast uncertainty using multiple model runs for specific locations and variables.

Instructions

Get ensemble forecasts showing forecast uncertainty with multiple model runs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latitudeYesLatitude in WGS84 coordinate system
longitudeYesLongitude in WGS84 coordinate system
modelsYesEnsemble models to use
hourlyNoHourly weather variables to retrieve
dailyNoDaily weather variables to retrieve
forecast_daysNoNumber of forecast days
temperature_unitNocelsius
wind_speed_unitNokmh
precipitation_unitNomm
timezoneNoTimezone for timestamps

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.3

TDQS

C2.9/5.0
Behavior2/5

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

No annotations provided. Description mentions 'forecast uncertainty' but does not specify how uncertainty is represented (e.g., percentiles, range), nor discloses update frequency, data source, or limitations.

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?

Single sentence, no fluff, but could be slightly longer to add value without losing conciseness.

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 10 parameters, no output schema, and no annotations, the description is insufficient for a complex ensemble tool. It omits explanation of available variables, output structure, and interpretation of uncertainty.

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 70%, so most parameters have basic descriptions. The tool's description adds no additional meaning beyond the schema. Baseline 3 is appropriate.

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 retrieves ensemble forecasts with uncertainty from multiple model runs. It distinguishes from the sibling 'weather_forecast' by emphasizing uncertainty, but does not differentiate from other model-specific siblings.

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 on when to use this tool versus alternatives like weather_forecast or model-specific tools. No scenarios or prerequisites mentioned.

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