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Glama

Openweather

by io.github.pipeworx-io

Current Weather

current_weather
Read-onlyIdempotent

Get the current weather for a city or coordinates: temperature, "feels like", conditions, humidity, wind speed, and cloud cover. Example: current_weather({ city: "London", units: "metric" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude. Use with lon instead of city.
lonNoLongitude. Use with lat instead of city.
cityNoCity name, optionally with country code, e.g. "London" or "London,GB". Provide this OR lat/lon.
unitsNoTemperature units: "metric" (C, default), "imperial" (F), or "standard" (K).
_apiKeyNoOptional — your own OpenWeatherMap API key for higher limits; omit to use the shared Pipeworx key.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "_apiKey": "your-openweather-api-key",
+    "city": "London",
+    "units": "metric"
+  },
+  {
+    "_apiKey": "your-openweather-api-key",
+    "lat": 51.5074,
+    "lon": -0.1278,
+    "units": "imperial"
+  }
+]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds behavioral detail by listing return fields and showing an example call, providing value beyond the structured annotations.

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

Conciseness5/5

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

The description is a single, efficient sentence plus an example. It is front-loaded with the main action and contains no extraneous information.

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

Completeness5/5

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

For a read-only retrieval tool with no output schema, the description sufficiently explains what data is returned and all parameters are well-documented. The example adds completeness, and annotations cover safety.

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

Parameters4/5

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

Schema coverage is 100% with thorough descriptions. The description adds a concrete example demonstrating the two input patterns (city vs lat/lon) and the units enum, providing practical usage context that aids understanding.

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

Purpose5/5

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

The description clearly states the tool retrieves current weather for a city or coordinates and lists specific data fields (temperature, feels like, conditions, humidity, wind speed, cloud cover). The example distinguishes it from siblings like forecast.

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

Usage Guidelines4/5

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

The description explicitly says to use for current weather, implies not for forecasts, and shows how to provide city vs coordinates and units. No explicit alternatives named, but sibling 'forecast' exists and the context is clear.

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

All Openweather toolsInspect
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TDQS

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions. However, 'ask_pipeworx' and 'ask_pipeworx_grounded' are very similar, and 'polymarket_arbitrage' and 'polymarket_edges' overlap in scope, which could cause confusion for an agent.

Naming Consistency3/5

Tool names mostly use snake_case but mix verb-first (e.g., 'compare_entities', 'resolve_entity') and noun-first (e.g., 'air_quality', 'entity_profile') patterns. Some names are single words ('forecast', 'geocode'), showing overall inconsistency.

Tool Count3/5

With 30 tools, the server covers many domains (weather, company info, betting, memory, subscriptions). While each tool serves a purpose, the count is on the higher side and could be streamlined, but it's not excessive given the diverse functionality.

Completeness4/5

The tool set provides comprehensive coverage for its domains: weather (current, forecast, air quality), company research (profile, compare, recent changes, validation), betting (research, arbitrage, edges), memory (CRUD), and subscriptions (CRUD). Minor gaps include no tool for editing subscriptions or deleting weather data, but these are outside the intended scope.

Resources