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neshan-mcp

neshan-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Neshan air quality

ns_air_quality
Read-onlyIdempotent

Retrieve today's air quality index for an Iranian city, including pollutant levels and station readings; use coordinates to get only the AQI.

Instructions

Get today's air quality index (AQI) of an Iranian city from Neshan, with pollutants and the readings of each station.

aqi is on the 0-500 scale (50 good, 100 acceptable, 150 sensitive-unhealthy, 200 unhealthy, 300+ very unhealthy/hazardous); status is Neshan's Persian label. stations are sorted most polluted first. A point returns only aqi. No data: try the province capital.

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": "ns_air_quality"
  }
}

Input Schema

NameRequiredDescriptionDefault
placeNoCity (English or Persian, e.g. 'Isfahan', 'bandar abbas') for the full report, or 'lat,lng' for just the index.Tehran

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only declare read-only/idempotent/open-world safety; the description goes well beyond by decoding the 0-500 AQI scale, noting that `status` is Neshan's Persian label, that `stations` are sorted most-polluted-first, that point queries return a reduced payload, and what to do when no data exists.

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?

Front-loaded with the core action, then tightly grouped into scale semantics, output shape, and fallback. The parenthetical AQI breakpoints are dense but directly aid interpretation of the returned number, so every sentence earns its place.

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?

A one-parameter tool with no output schema, yet the description still names the returned fields (aqi, status, pollutants, stations), their ordering, and the degraded point-mode response. Nothing an agent needs to call or interpret the result is missing.

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 already 100% (the `place` param documents city vs 'lat,lng' and the Tehran default), so the baseline is 3; the description adds real meaning by explaining the consequence of each mode — a point returns only `aqi`, whereas a city returns full pollutants and stations.

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?

States a specific verb (get), resource (today's air quality index / AQI), source (Neshan), and scope (Iranian city, including per-station readings). No sibling tool (reviews, photos, nearby, route, etc.) covers air quality, so it is unambiguously distinct.

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?

Clear conditional guidance: use a city name for the full report, a 'lat,lng' point for just the index, and 'No data: try the province capital' as a fallback. It doesn't name any sibling alternative, but no sibling overlaps in function, so there is little to route against.

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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