api_weatherCurrent weather + 7-day forecast by city name or lat/lon (open-meteo, no key needed). ?city=Moscow [HTTP x402 price: $0.002]
| Name | Required | Description | Default |
|---|---|---|---|
| params | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / params / additionalPropertiesRemoved value: -trueInput schema / properties / params / propertiesAdded value: +{
+ "city": {
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null
+ }
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the behavioral disclosure burden. It usefully states that open-meteo is the source, no API key is needed, and the call costs $0.002. However, it does not clarify failure behavior, invalid-city handling, rate limits, or how the lat/lon claim maps to the actual schema.
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 compact sentence that packs in the purpose, input types, data source, authentication requirement, example query, and cost. There is no filler or redundant repetition of the tool name or schema.
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?
For a simple read-only weather API with an output schema present, the description covers many essentials: source, auth, input example, and price. The main completeness gap is the unsupported/unclear lat/lon input, which could prevent an agent from correctly invoking the tool for coordinate-based queries.
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 0%, so the description must compensate. It does add value by giving a concrete URL-style example (?city=Moscow) and stating that city name or lat/lon are valid inputs. However, the lat/lon path is not explained, and the input schema only exposes a city parameter, creating ambiguity.
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 identifies the tool's purpose: current weather plus a 7-day forecast, with city name or lat/lon as input. The title alone would not convey this scope, and the description is specific enough to distinguish the tool from the sibling list, even though no explicit sibling comparison is made.
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?
It provides clear context for when to use the tool: whenever current weather or a 7-day forecast is needed. There are no explicit when-not-to-use conditions or alternative tool references, but no sibling tool appears to be a weather alternative, so the guidance is sufficient for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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44 tools is well over the 25+ threshold for a well-scoped set, making the server feel like a grab-bag of unrelated utilities. Even though each tool is small and individually useful, the overall surface is too large and would benefit from consolidation into focused sub-servers.
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