Get current weather for any city or coordinates worldwide. Returns temperature, humidity, wind, and conditions.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | Latitude (alternative to location) | |
| lon | No | Longitude (alternative to location) | |
| location | No | City name (e.g. 'Toronto', 'London', 'Tokyo') |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes safe read-only behavior, and the description adds valuable context by stating the return payload (temperature, humidity, wind, conditions) and geographic scope. No contradictions or destructive behavior to disclose.
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?
A single sentence conveys purpose and return values with zero filler. The structure is front-loaded with the action, then the scope, then the output—all in one efficient line.
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?
With no output schema, the description appropriately enumerates the key return fields (temperature, humidity, wind, conditions). For a low-complexity read-only tool with completely documented optional parameters, this is sufficiently complete, though units (e.g., Celsius vs Fahrenheit) are not specified.
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 coverage for all three parameters is 100%, so the schema already documents lat, lon, and location. The description adds no new parameter-level meaning beyond acknowledging both city and coordinate inputs, which is redundant with the schema descriptions.
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 starts with a specific verb+resource ('Get current weather') and clearly scopes it to any city or coordinates worldwide. This unambiguously distinguishes it from sibling tools like currency and translate, which are unrelated 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 implicitly signals when to use the tool (for weather queries) and its worldwide coverage. Since there are no competing weather tools among siblings, no explicit exclusions are necessary, though it doesn't explicitly state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct capability: chat, embeddings, image generation, speech synthesis, transcription, currency exchange, translation, and weather. There is no overlap or ambiguity between them.
The five AI tools follow a consistent 'ai_' prefix pattern (ai_chat, ai_embeddings, etc.), but the three utility tools (currency, translate, weather) break this convention, creating a minor inconsistency.
With 8 tools, the server is well-scoped for a multi-purpose AI and utility toolkit. The count is neither too sparse nor overly heavy, and each tool has a clear role.
The toolset covers a broad range of AI modalities (text, embedding, image, audio) plus common utilities (currency, translation, weather). Minor gaps exist, such as video generation or web search, but these are not essential for the apparent scope.