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hesscl

census-geocoding-mcp

by hesscl

geocode_pr_address

Convert a single Puerto Rico address to geographic coordinates, including Urbanization and Municipio fields. Provide street plus ZIP or city/state, or street plus urb and municipio.

Instructions

Geocode a single Puerto Rico address with support for Urbanization and Municipio fields. To submit a PR address without Urbanization, provide at minimum street + zip OR street + city + state. To submit with Urbanization, provide at minimum street + urb + municipio. State is always PR.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urbNoUrbanization name, e.g. 'Urb San Juan' or 'San Juan'
zipNoZIP code (should begin with 006, 007, or 009)
cityNoCity name
streetYesHouse number and street name, e.g. '1234 Main St'
benchmarkNoBenchmark name or ID (default: "Public_AR_Current")
municipioNoMunicipio name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A3.6/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses that state is always PR and the real field-combination requirements (beyond the schema's misleadingly minimal 'street only'), but says nothing about return values, match quality, or error behavior.

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?

Three tight sentences, each earning its place, with the core purpose front-loaded and the input rules following immediately. No 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?

With no annotations and no output schema, the description fully covers input requirements but leaves the return value undocumented. For a geocoding tool this is a moderate gap, though the standard geocode response makes it tolerable.

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 adds genuine value the schema cannot express: the conditional dependency between parameters (street+zip OR street+city, or street+urb+municipio) and the implied constant 'state = PR' that is not even a schema property.

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 states a specific verb and resource ('Geocode a single Puerto Rico address') and names the distinguishing features (Urbanization, Municipio support). It differentiates itself by PR-specificity, though it does not explicitly contrast with siblings like geocode_parsed_address or geocode_oneline_address.

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 gives concrete input-combination rules for two scenarios (with and without Urbanization), which implies how to invoke the tool. However, it never states when to prefer this tool over the sibling geocoders, nor any exclusions, so usage is only partially guided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.