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FauxGen MCP

by LazyInvestor
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TypeScript
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Generate fake address

generate_address

Generate a fictional street address for a given country using ISO country codes. Useful for testing forms, seeding sample data, and creating mock user profiles.

Instructions

Generate a street address for a country.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNoISO country code used on fauxgen.com. One of: us, gb, ca, au, nz, ie, in, pk, ng, za, gh, np, hk, ph, de, at, ch, fr, be, lu, es, mx, pt, br, it, nl, ru, by, kz, ua, pl, cz, sk, hu, ro, md, gr, tr, hr, si, rs, mk, bg, my, sg, se, no, dk, fi, lv, il, ae, sa, eg, ir, am, ge, az, jp, kr, cn, tw, th, vn, id, snus

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 behavioral burden, yet it discloses nothing beyond the act of generation: no randomness/determinism note, no indication that output is synthetic fake data, no auth or rate-limit context, and no description of the returned value.

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?

A single short, front-loaded sentence with no filler. It is efficient, though the terseness borders on under-specification rather than true conciseness.

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?

For a simple one-optional-parameter generator with no output schema, the definition is adequate but incomplete: it never states what is returned (a street address string?) or that the default country is 'us', both of which matter when there is no output schema to fall back on.

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 coverage is 100% and the country parameter's description already enumerates every accepted ISO code and the default of 'us', so the description's 'for a country' adds no information beyond the schema. Baseline 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?

States a specific verb (Generate) and resource (street address) plus a scoping dimension (for a country). This clearly distinguishes it from sibling generators like generate_email or generate_name, though it never names a sibling explicitly.

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 when-to-use, when-not-to-use, or alternative guidance is given. The reader can infer this is for producing synthetic address data, but that is implied at best and nothing distinguishes it from the other fauxgen generators.

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

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