jp-address-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@jp-address-mcpNormalize this address: 東京都新宿区西新宿2-8-1 パークタワー1503号"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Japanese Address Normalizer & Verifier (MCP Server)
An MCP server that normalizes and verifies Japanese postal addresses. Splits messy Japanese address strings (full-width characters, mixed hyphens, romaji, building/room names) into structured fields, with a verification flag and lat/lng.
Built for AI agents doing cross-border commerce, logistics, or CRM involving Japan.
Endpoint (remote, no install)
Streamable HTTP:https://jp-addr.streamfront.net/mcp
Related MCP server: mcp-server-zipcode-jp
Tool
normalize_jp_address
Structure & verify a raw Japanese address string.
Input: { "address": "東京都新宿区西新宿2-8-1 パークタワー1503号" }
Output (example):
{
"ok": true,
"normalized": {
"pref": "東京都", "city": "新宿区", "town": "西新宿二丁目",
"banchi": "8-1", "building": "パークタワー", "room": "1503"
},
"geo": { "lat": 35.68945, "lng": 139.691774 },
"level": 3, "verified": true
}How it works
Wraps the open-source @geolonia/normalize-japanese-addresses engine and
adds a preprocessing/structuring layer: full-width→half-width, hyphen
normalization, chome/banchi boundary detection via engine metadata,
building & room separation, and a verification flag.
Status
Early. Single tool. Tested mainly on residential/urban addresses. Feedback welcome.
Registry
Published to the official MCP Registry as net.streamfront/jp-address.
Available Tools
1 toolnormalize_jp_addressA
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. Use whenever you need to register, validate, or route a Japanese address reliably.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Raw Japanese address string to normalize. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool splits addresses into structured fields, returns a verification flag and lat/lng, and handles full-width characters, mixed hyphens, romaji, and building/room separation. This adds meaningful behavioral context beyond the schema, though it does not cover potential error cases or side effects.
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 concise and well-structured: the first sentence states the core purpose, the second elaborates on outputs, and the third covers input handling and usage. Every sentence contributes actionable information with no padding.
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 tool with one parameter and no output schema, the description is quite complete. It explains what the tool returns (verification flag, lat/lng) and the structured fields extracted. However, it does not mention potential failure modes or how the verification flag behaves, leaving minor gaps for a normalization/verification tool.
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?
The schema documents the single 'address' parameter with 100% coverage, so the baseline is 3. The description adds semantic value by explaining the types of messy input accepted (full-width, hyphens, romaji) and the tool's ability to separate building/room, providing practical guidance beyond the schema's generic description.
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 with specific verbs: 'Normalize and verify a Japanese postal address.' It details the structured output fields (prefecture, city, town, block number, building, room), verification flag, and lat/lng, effectively distinguishing it from generic parsers by mentioning its handling of messy input.
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 provides explicit use cases: 'Use whenever you need to register, validate, or route a Japanese address reliably.' It gives clear context for when to use it, though it does not mention when not to use it or list alternatives (likely because no siblings exist).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
1 tool update
v0.1.0- First observed
normalize_jp_address
TDQS
Only one tool exists, so there is no possibility of confusion. The tool's purpose is unambiguous and clearly described.
The single tool name follows a clear verb_noun pattern (normalize_jp_address), which is predictable and consistent with common conventions.
With only one tool, the server feels minimal for a dedicated address utility. It earns its place, but the scope is thin and borderline.
The tool consolidates parsing, verification, and geocoding into one operation, covering the full address normalization workflow. There are no obvious gaps for the stated purpose.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Normalize and verify Japanese postal addresses into structured fields for agents.
Verify Japanese companies, invoice-issuer registrations and addresses against government open data.
Address validation & geocoding for AI agents: 240+ countries, UK PAF, free US/CA enrichment
Japan data tools for AI agents: calendar (rokuyo), address, name splitting, corporate number lookup
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