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 states the tool 'Get[s]' data, implying a read-only operation, but doesn't address key behavioral aspects such as rate limits, authentication requirements, data freshness, error handling, or response format. For a tool with 7 parameters and no output schema, this is a significant gap in transparency.

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 directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly. Every part of the sentence contributes essential information, earning its place.

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 complexity (7 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, usage context, and output expectations, which are crucial for effective tool invocation. While the schema covers parameters well, the description doesn't compensate for missing annotations or output schema, leaving gaps in overall understanding.

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?

The description adds no specific parameter information beyond what the input schema provides. Since schema description coverage is 100%, the schema already documents all parameters thoroughly (e.g., latitude/longitude ranges, daily enum values, past_days/forecast_days limits). The baseline score of 3 is appropriate as the schema does the heavy lifting, but the description doesn't enhance parameter understanding with additional context or examples.

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 river discharge and flood forecasts from GloFAS (Global Flood Awareness System).' It specifies the action ('Get'), resource ('river discharge and flood forecasts'), and data source ('GloFAS'), which is specific and informative. However, it doesn't explicitly differentiate from siblings like 'weather_forecast' or 'ensemble_forecast', which might also provide forecast data, though the focus on river/flood data is implied.

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. It doesn't mention any prerequisites, exclusions, or comparisons to sibling tools such as 'weather_forecast' or 'climate_projection', leaving the agent to infer usage based on the purpose alone. This lack of explicit context reduces its effectiveness in tool selection.

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