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jakobautomation

agentsvc-mcp

geocode

Convert city names or postal codes to latitude/longitude, or find nearest place and postal code from coordinates.

Instructions

Geocoding — Geocoding and reverse geocoding from GeoNames: city, town or postal code to lat/lon, and lat/lon to the nearest place and postal code. Covers 170,000 places with 1000+ inhabitants and 1.8 million postal codes worldwide, answered from our own database in milliseconds. Not street level: house numbers and streets are skipped and reported in ignored_parts. Provide address (e.g. 'Paris, Texas', '10115 Berlin') or lat + lon. Cost: $0.003 USDC per call. Latency p99: 300ms.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the burden and discloses data source, coverage size, cost per call, p99 latency, and the fact that non-geocodable parts are reported in ignored_parts. It omits auth requirements, rate limits, and error behavior, but otherwise provides rich operational context.

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

Conciseness4/5

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

The description is front-loaded with purpose and scope, then moves to limitations, inputs, cost, and latency. It is slightly verbose with coverage statistics and duplication in the opening phrase, but each sentence contributes useful information.

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

Completeness4/5

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

For a utility geocoder with no annotations and no output schema, the description covers purpose, inputs, limitations, cost, and latency well enough to invoke correctly. It does not detail return fields beyond ignored_parts, but the absence of an output schema lowers the burden.

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%, so the input schema already documents parameters with examples and the oneOf address vs lat+lon structure. The description adds example addresses but no meaningful semantics beyond what the schema provides, making the baseline 3 appropriate.

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?

The description clearly states forward and reverse geocoding from city/town/postal code to lat/lon and vice versa, with explicit scope and examples. It does not, however, name or differentiate against sibling tools such as postal_code, so it falls short of the full sibling-differentiation criterion.

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?

It gives clear usage conditions for the two modes (provide address for forward geocoding, or lat + lon for reverse geocoding) and an explicit exclusion: not street level, with house numbers and streets skipped. It does not name alternative tools to use when street-level or other needs arise.

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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