Open-Meteo MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'high-resolution data for Nordic countries,' which adds some context about data quality and regional focus, but fails to address critical aspects like rate limits, authentication needs, error handling, or what the response format looks like. For a tool with 11 parameters and no output schema, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence earns its place by specifying the action, source, data quality, and geographic scope.

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

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

Given the tool's complexity (11 parameters, no annotations, no output schema, and multiple sibling alternatives), the description is incomplete. It lacks usage guidelines, behavioral details (e.g., rate limits, response format), and differentiation from other weather tools. The high parameter count and absence of output schema mean the description should do more to guide effective use.

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

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

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain the meaning of 'high-resolution' in relation to parameters like 'hourly' or 'forecast_days'). Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get weather forecast from Norwegian weather service with high-resolution data for Nordic countries.' It specifies the action ('Get weather forecast'), the data source ('Norwegian weather service'), and the geographic focus ('Nordic countries'). However, it doesn't explicitly differentiate from sibling tools like 'weather_forecast' or 'meteofrance_forecast' beyond mentioning the Norwegian source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple weather-related sibling tools (e.g., 'weather_forecast', 'dwd_icon_forecast', 'meteofrance_forecast'), there's no indication of when this Norwegian service is preferred, what makes it unique, or any prerequisites for use.

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