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Ziplore: US ZIP Code API (county, time zone, demographics, radius)

Look up US ZIP codes

zip_lookup
Read-onlyIdempotent

City, state, county and FIPS, coordinates, time zone with UTC offset, and Census demographics (population, income, home value, rent) for up to 10 US ZIP codes. Accepts ZIP+4, addresses and ZIPs missing a leading zero.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipsYesUS ZIP codes (ZIP+4, addresses and ZIPs that lost their leading zero are accepted). Up to 10.
demographicsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds input flexibility (ZIP+4, addresses, missing leading zero) but does not disclose additional behavioral traits such as rate limits, permission requirements, or output variability. Since annotations already cover the core safety, this is adequate but not rich.

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?

The description is a single, well-structured sentence that front-loads the main purpose and then lists the key output fields. There is zero redundancy, and every phrase contributes meaning. The format is clear and easy to parse quickly.

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 tool with no output schema and two parameters (one optional), the description provides a comprehensive list of return fields, input flexibility, and the purpose. It is missing explicit clarification on the demographics boolean's behavior, but the overall information is sufficient for an agent to call the tool correctly and understand the expected output.

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 50%: the 'zips' parameter is fully described in the schema, while 'demographics' has no schema description. The description mentions 'Census demographics' as part of the output, which gives partial meaning to the demographics flag, but it does not explicitly explain what the boolean toggles or its effect on the response. It adds some value beyond the schema but doesn't fully compensate for the uncovered parameter.

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 clearly states a specific verb (look up) and resource (US ZIP codes), and enumerates the exact fields returned (city, state, county, FIPS, coordinates, time zone, demographics). This distinguishes it from siblings like nearest_zip or zip_distance, which perform different operations. The purpose is unambiguous and specific.

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?

The description implies usage when you have ZIP codes and need their details, but it does not explicitly differentiate from the sibling tools or state conditions for when to choose this tool over alternatives. It doesn't mention exclusions like 'use nearest_zip for location-based queries.' The context is clear but not explicit.

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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