lazymac-mcp

k_address_tools

Normalize, parse, validate, geocode, and find postal codes for Korean addresses to ensure accurate location data and formatting.

Instructions

Korean address normalize, parse, validate, geocode, postal code

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "k_address_tools"
  }
}

Input Schema

Name	Required	Description	Default
`params`	No	Free-form params object — passed as query string for GET, JSON body for POST

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Apr 15, 2026

TDQS

C2.6/5.0

Behavior2/5

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

With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions operations (normalize, parse, etc.) but doesn't disclose critical traits like rate limits, authentication needs, error handling, or output format. For a tool with potentially complex address processing, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a concise list of functions without unnecessary words. However, it's not front-loaded with a clear primary purpose, and the lack of structure (e.g., bullet points or prioritization) makes it less effective despite brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter (a nested object), no annotations, no output schema, and multiple implied functions, the description is incomplete. It doesn't clarify input formats, output expectations, or error conditions, leaving significant gaps for an AI agent to infer usage.

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

Parameters3/5

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

Schema description coverage is 100%, but the schema only documents a generic 'params' object without specifics. The description adds no parameter details beyond the schema, failing to explain what parameters are needed for each function (e.g., address string for geocode). Baseline 3 applies due to high coverage, but value added is minimal.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description lists functions (normalize, parse, validate, geocode, postal code) but lacks a clear verb+resource structure and doesn't distinguish from sibling 'k_address_geocoder'. It's vague about what specific Korean address operations it performs and how they differ from the dedicated geocoder tool.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like 'k_address_geocoder' or 'ip_geolocation'. The description implies multiple functions but doesn't specify contexts for each (e.g., when to normalize vs. geocode). No prerequisites or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.