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neshan-mcp

neshan-mcp

by sepehr071
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Address of a point on Neshan

ns_reverse_geocode
Read-onlyIdempotent

Convert latitude and longitude coordinates into a street-level Persian address and province name for Iranian locations.

Instructions

Turn a latitude/longitude into Neshan's street address and province (reverse geocoding).

The address is street-level Persian text without city or postal code; street is the named road at the point. For name to coordinates use ns_search.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "location": "<location>"
    },
    "name": "ns_reverse_geocode"
  }
}

Input Schema

NameRequiredDescriptionDefault
locationYesThe point as 'lat,lng', e.g. '35.7270,51.3793'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and openWorld, so the safety profile is covered. The description adds value beyond them by disclosing the shape of the result: street-level Persian text, no city or postal code, and that `street` is the named road at the point — which pre-empts a real misinterpretation of the return value. It stops short of saying what happens for points outside coverage or in water/desert, but that is a modest gap given the rich 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?

Two short paragraphs: the first states the operation and its output character, the second routes to the alternative tool. Nothing is repeated and the most decision-relevant content (what you get back, and the inverse tool) is front-loaded.

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 single-parameter read tool with full annotation coverage, the definition covers the direction of conversion, the nature of the returned address, and the alternative sibling. No output schema exists, yet the description still characterizes the payload well enough that an agent knows what to expect.

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

Parameters3/5

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

Schema description coverage is 100%, and the schema already specifies the "lat,lng" string format with a worked example. The description only echoes "latitude/longitude", adding no ordering, precision, or coordinate-system guidance beyond what structured data provides, so baseline 3 applies.

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 opens with a specific verb-and-resource pairing ("Turn a latitude/longitude into Neshan's street address and province") and names the domain term "reverse geocoding". The orientation detail ("street-level Persian text without city or postal code") and the explicit contrast with ns_search make it distinguishable from every sibling at a glance.

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?

"For name to coordinates use ns_search" gives an explicit alternative and the condition that selects it, which is the main routing ambiguity for a geocoder. It does not address the other plausible confusions among siblings — e.g. when to prefer ns_nearby or ns_place for point-of-interest lookups versus a raw address — so the guidance is clear but not exhaustive.

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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