address-to-zip
Server Details
日本の住所と郵便番号を相互変換するMCPサーバー。住所から郵便番号を検索、郵便番号から住所を逆引きします。
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.7/5 across 2 of 2 tools scored.
The two tools serve distinct and opposite purposes: one converts zip code to address, the other converts address to zip code. There is no overlap or ambiguity.
Both tools use snake_case with a clear verb_noun pattern (lookup_zipcode, search_address), providing consistent and predictable naming.
For a focused address-to-zip conversion server, two tools perfectly cover the forward and reverse lookups. This is an appropriate and well-scoped number.
The domain is fully covered with the two fundamental operations: zip code to address and address to zip code. There are no missing operations or dead ends.
Available Tools
2 toolslookup_zipcodeAInspect
郵便番号から住所を逆引きする。100-0005 または 1000005 形式に対応(全角数字・ハイフン有無は不問)。
| Name | Required | Description | Default |
|---|---|---|---|
| zipcode | Yes | 郵便番号(例: 100-0005 または 1000005。全角数字・ハイフン有無も可) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions input format flexibility but does not disclose what happens if the zip code is invalid or not found, nor does it describe the response structure. It is adequate but lacks depth.
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 exceptionally concise with two sentences, no filler, and clearly states the tool's purpose and input format. Every word adds value.
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?
Given the tool's simplicity (one parameter, no output schema), the description covers essential usage. A minor gap is the lack of return value description, but for a straightforward lookup, it is mostly complete.
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?
Schema description coverage is 100%, so the schema already documents the zipcode parameter in detail. The description adds minimal new meaning beyond confirming format flexibility, which is already in the schema.
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 clearly states the tool does a reverse address lookup from a zip code, and specifies supported formats. However, it does not explicitly differentiate from the sibling tool 'search_address', which likely performs a forward lookup.
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?
The description implies usage when you have a zip code and need an address, but provides no explicit guidance on when not to use, prerequisites, or how this tool contrasts with the sibling 'search_address'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_addressAInspect
日本の住所文字列から郵便番号を検索する。番地・建物名付きでも町名まで解釈する。
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 返却件数の上限(1-50・既定10) | |
| address | Yes | 検索する住所(例: 東京都千代田区丸の内) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states basic function but does not disclose behavior for unmatched addresses, multiple results, authentication needs, or rate limits.
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 a single concise sentence with no wasted words. It effectively communicates the tool's core functionality.
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 tool with 2 parameters and no output schema, the description is adequate but lacks details on return values or error handling. It is minimally viable.
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?
Schema covers 100% of parameters with descriptions. The description adds value beyond schema by explaining that the address parameter can handle detailed formats including building names, which aids correct usage.
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 clearly states the tool searches for postal codes from Japanese address strings, with a specific verb and resource. The sibling tool 'lookup_zipcode' likely does the reverse, so the purpose is distinct.
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?
No explicit guidance on when to use this tool versus the sibling 'lookup_zipcode'. The description implies its usage scenario but does not provide exclusions or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$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.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
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
The URL of the server is wrong
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.
Discussions
No comments yet. Be the first to start the discussion!