air_qualityGet the current air quality for a set of coordinates: an air quality index (AQI, 1=Good to 5=Very Poor) plus pollutant component concentrations (CO, NO2, O3, PM2.5, PM10, etc.). Example: air_quality({ lat: 51.5, lon: -0.12 })
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude. | |
| lon | Yes | Longitude. | |
| _apiKey | No | Optional — your own OpenWeatherMap API key for higher limits; omit to use the shared Pipeworx key. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "_apiKey": "your-openweather-api-key",
+ "lat": 51.5074,
+ "lon": -0.1278
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds behavioral context by specifying return data (AQI scale and pollutants) and showing example usage. No contradictions.
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 two sentences plus an example, highly efficient and front-loaded with key information. No extraneous details.
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 low-complexity tool with 3 parameters and no output schema, the description sufficiently covers purpose, return format, and usage. Minor omission: no units for pollutant concentrations, but overall adequate.
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 is 100%, so baseline is 3. The description adds marginal value by showing example values and explaining AQI scale, but does not provide significant additional parameter meaning beyond what the schema offers.
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 retrieves current air quality for given coordinates, returning AQI and pollutant concentrations. It uses a specific verb ('Get') and resource ('air quality'), and is distinct from sibling tools like current_weather.
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 an explicit example and mentions optional API key usage. While no direct 'when not to use' is stated, the tool's specificity to air quality makes its purpose clear relative to siblings.
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.
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.
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.
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.
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.