jp-address
Server Details
Normalize and verify Japanese postal addresses into structured fields for agents.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.4/5 across 1 of 1 tools scored.
Only one tool exists, so there is no possibility of ambiguity between tools.
With a single tool, naming is consistent by definition; the name clearly describes its function.
One tool is minimal but appropriate for a focused server that normalizes Japanese addresses; it covers the core use case without being excessive.
The tool provides thorough address normalization (splitting, verification, lat/lng), but lacks additional operations like searching or listing, which are minor gaps for its stated purpose.
Available Tools
1 toolnormalize_jp_addressAInspect
Normalize and verify a Japanese postal address. Splits a raw Japanese address string into structured fields (prefecture, city, town, block number, building, room) and returns a verification flag plus lat/lng. Handles messy input: full-width chars, mixed hyphens, romaji, and building/room separation that generic parsers miss.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Raw Japanese address string. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It discloses the tool's behavior: splitting addresses, returning structured fields, verification flag, and lat/lng. It also mentions handling specific messy input types. Minor gap: does not describe error handling for invalid addresses.
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 two sentences: the first states core purpose and outputs, the second adds crucial handling details. No unnecessary words; every sentence is informative and earns its place.
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 one parameter, no output schema, and no sibling tools, the description is fairly complete. It explains the input type, the tool's actions, and the types of outputs. It could be slightly more specific about the return structure (e.g., field names), but overall it provides sufficient context for an agent.
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 coverage is 100% with one parameter 'address' described as 'Raw Japanese address string.' The description adds value by specifying that the tool handles full-width characters, mixed hyphens, romaji, and building/room separation, which clarifies the input's acceptable variety beyond 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's purpose: 'Normalize and verify a Japanese postal address.' It specifies actions (normalize, verify, split into structured fields) and outputs (verification flag, lat/lng). Even without siblings, it distinguishes itself as a specialized Japanese address parser.
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 indicates when to use this tool: for messy input including full-width chars, mixed hyphens, romaji, and building/room separation that generic parsers miss. This provides clear context, but it does not explicitly state when not to use it or mention any alternative tools.
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.
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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
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.
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