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 full burden. It mentions 'forecast data' but doesn't disclose behavioral traits like rate limits, authentication needs, data freshness, or whether this is a read-only operation. The description is minimal and lacks context about what the tool actually does beyond the basic purpose.

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 states the core purpose. It's appropriately sized for a simple data retrieval tool, though it could be slightly more informative without losing conciseness. No wasted words or redundant information.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what format the data returns, whether it's real-time or historical, or any limitations. For a tool with 6 parameters and environmental data complexity, more context about behavior and output would be helpful for an AI agent.

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 fully documents all 6 parameters. The description adds no parameter-specific information beyond mentioning some pollutants that map to the 'hourly' enum values. It doesn't explain parameter interactions or provide additional context, meeting the baseline for high schema coverage.

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 air quality forecast data including PM2.5, PM10, ozone, nitrogen dioxide and other pollutants.' It specifies the verb ('Get') and resource ('air quality forecast data') with examples of pollutants. However, it doesn't explicitly differentiate from sibling tools like 'weather_forecast' or 'climate_projection' which might overlap in environmental data domains.

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 sibling tools or clarify specific use cases (e.g., air quality vs. general weather forecasting). The agent must infer usage from the name and description alone, with no explicit when/when-not instructions.

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