Free, keyless postal/ZIP code lookup: place name(s), state/region, and coordinates.
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Average 5/5 across 1 of 1 tools scored.
With only one tool, there is no possibility of confusion between tools. The tool's purpose is clearly defined and distinct from any hypothetical alternatives.
The single tool name 'lookup_postal_code' follows a clear verb_noun pattern, and since there is only one tool, there are no inconsistencies or mixed conventions.
The server offers only one tool, which feels too few for the broad scope of 'postal lookup'. A more complete set would at least include a reverse lookup (place to postal code) or validation, so the single tool is thin.
The tool covers the core function of resolving postal codes to places, but the description explicitly excludes reverse lookup and full address lookup, which are natural expectations for a postal lookup server. These gaps are notable but not catastrophic since the primary forward lookup is well implemented.
lookup_postal_codeAResolve a postal/ZIP code to its place name(s), state/region, and
coordinates. country_code is a 2-letter ISO code (US, GB, DE, ...);
postal_code format varies by country (e.g. "90210" for the US,
"SW1A 1AA" style outward codes for the UK). Use for "what city is ZIP
90210 in", "where is postal code X in country Y", or any question
that needs a place name/region/lat-lon from a postal code -- not for
the reverse (place name to postal code) or for full street address
lookup. Some postal codes span multiple places, in which case all of
them are returned. Returns an error dict (never raises) if the code
isn't recognized for that country.
| Name | Required | Description | Default |
|---|---|---|---|
| postal_code | Yes | ||
| country_code | Yes |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds substantive behavior beyond the readOnlyHint annotation: multi-place results are returned when a postal code spans multiple places, and errors are returned as a dict rather than raised. These details help an agent predict tool behavior without invoking it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact yet information-dense, front-loading the core purpose and then efficiently covering parameter formats, usage guidance, edge-case behavior, and error handling. No sentence is wasted or redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter lookup with an output schema and readOnlyHint, the description covers all essential aspects: purpose, parameter semantics, reverse-lookup exclusion, multi-result behavior, and error handling. The presence of an output schema makes the lack of explicit return-value documentation acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining `country_code` as a 2-letter ISO code with examples and `postal_code` as country-dependent with format examples ('90210' vs 'SW1A 1AA'). This is exactly the semantic context the bare schema lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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: 'Resolve a postal/ZIP code to its place name(s), state/region, and coordinates.' It clearly distinguishes from reverse lookup and full address lookup, making the tool's purpose unmistakable even with no siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit when-to-use examples are given ('what city is ZIP 90210 in') and when-not-to-use cases are stated ('not for the reverse... or full street address lookup'). This gives an agent clear decision criteria for selecting this tool.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
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The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
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Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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