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sg-haze-rain-mcp

sg-haze-rain-mcp

by ericwang915
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Singapore weather forecast

get_forecast

Retrieve Singapore NEA air-quality and rainfall forecasts for a caller's location or chosen region, with 2-hour, 24-hour, or 4-day horizons.

Instructions

NEA forecast for the caller's area/region. horizon: '2h' (area nowcast), '24h' (default; general + regional periods) or '4d' (island-wide outlook).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_forecast"
  }
}

Input Schema

NameRequiredDescriptionDefault
ipNoGeolocate this IP instead of the machine's own public IP.
latNoLatitude, if the caller already knows where they are (skips IP lookup).
lonNoLongitude, paired with lat.
langNoLanguage for labels and health advice. Defaults to SG_HAZE_LANG or 'en'.
regionNoForce a PSI region instead of locating the caller: north, south, east, west or central.
horizonNoForecast horizon. Default 24h.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses the default location source (caller's area) and horizon semantics, which is useful, but says nothing about read-only nature, response size/format, or behavior when geolocation fails.

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?

Two compact sentences, front-loaded with the resource and scope, followed immediately by the horizon mapping. Every clause carries information; nothing is filler.

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

Completeness3/5

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

For a 6-parameter read tool with no annotations and no output schema, the description covers the horizon and location dimensions well but omits any indication of what the response looks like or what happens with the PSI region/haze-related fields. Adequate but with a clear gap around return values.

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%, so the baseline is 3, but the description genuinely enriches the horizon parameter beyond the schema's terse 'Forecast horizon. Default 24h.' by explaining what each value returns (area nowcast vs general/regional periods vs island-wide outlook).

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

Purpose4/5

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

States a specific verb+resource: 'NEA forecast for the caller's area/region', which tells the agent exactly what it returns and whose location it uses. It doesn't explicitly distinguish itself from siblings like weather_now or get_rain, so sibling differentiation is left implicit.

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

Usage Guidelines3/5

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

It names the three horizon values and marks 24h as the default, which implies the choice depends on the lookahead needed. But it never says when to prefer this over weather_now or get_rain, and gives no exclusions or prerequisites.

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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