lazymac-mcp

ip_geolocation

Get location data for IP addresses including country, city, coordinates, timezone, ISP, and ASN information.

Instructions

IP → country, city, coordinates, timezone, ISP, ASN

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": "ip_geolocation"
  }
}

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

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It lists output fields but doesn't describe how the tool behaves: e.g., whether it requires authentication, rate limits, error handling, or data freshness. For a tool with no annotation coverage, this is a significant gap in transparency.

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

Conciseness5/5

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

The description is extremely concise and front-loaded, using a compact 'IP →' notation followed by a comma-separated list of output fields. Every element (arrow symbol, field names) earns its place by conveying core functionality without waste. It's appropriately sized for a simple lookup tool.

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

Completeness3/5

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

Given the tool's low complexity (single parameter, no output schema, no annotations), the description is somewhat complete but lacks depth. It covers the basic purpose and output fields but misses behavioral details (e.g., how to structure inputs, error cases). For a tool with minimal structured data, it should provide more context to compensate.

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?

The input schema has 100% description coverage, documenting a single 'params' object as free-form parameters passed in queries or JSON. The description adds no parameter-specific information beyond what the schema provides, such as expected keys (e.g., 'ip') or formats. With high schema coverage, the baseline score of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool's function: converting an IP address to geographic and network information (country, city, coordinates, timezone, ISP, ASN). It uses a concise 'IP →' format that implies transformation. However, it doesn't explicitly differentiate from sibling tools like 'k_address_geocoder' or 'timezone', which might offer overlapping functionality.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, limitations, or comparisons to sibling tools like 'k_address_geocoder' (which might handle addresses instead of IPs) or 'timezone' (which might provide timezone data independently). Usage context is implied but not explicit.

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