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PostalDataPI

PostalDataPI MCP Server

lookup_postal_code

Find city, state, and region details for postal codes in 70+ countries including US ZIP codes, UK postcodes, and German PLZ codes.

Instructions

Look up a postal code and get city, state, and region information.

Works for ZIP codes (US), postcodes (UK), PLZ (Germany), and postal codes in 70+ countries. Use this when someone asks about a postal code, wants to know what city a ZIP code belongs to, or needs address information.

Args: postal_code: The postal code to look up (e.g., "90210", "SW1A", "10115", "100-0001") country: ISO 3166-1 alpha-2 country code (e.g., "US", "GB", "DE", "JP"). Defaults to "US".

Returns: City, state/region, and abbreviation for the postal code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
postal_codeYes
countryNoUS

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses behavioral traits such as the tool's international scope (works for 70+ countries) and default behavior (country defaults to 'US'), which are useful beyond basic functionality. However, it doesn't mention error handling, rate limits, or authentication needs, leaving some gaps.

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 appropriately sized and front-loaded: the first sentence states the purpose, followed by scope, usage guidelines, and parameter details. Every sentence adds value, with no wasted words, making it efficient and well-structured.

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?

Given the tool's moderate complexity, no annotations, and an output schema (which handles return values), the description is complete enough. It covers purpose, usage, parameters, and scope, providing all necessary context for an agent to use the tool effectively without redundancy.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It adds significant meaning beyond the input schema by explaining what 'postal_code' and 'country' represent, providing examples (e.g., '90210', 'US'), and noting the default for country. This fully documents the parameters in a helpful way.

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 the verb 'look up' and resource 'postal code', specifying it retrieves city, state, and region information. It distinguishes from siblings by focusing on lookup rather than metadata retrieval, validation, or city-based search, making it specific and differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: 'when someone asks about a postal code, wants to know what city a ZIP code belongs to, or needs address information.' It also implies alternatives by listing sibling tools like get_postal_code_metadata, search_by_city, and validate_postal_code, though it doesn't name them directly, the context is clear.

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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