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FauxGen MCP

FauxGen MCP

by LazyInvestor
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Generate fake identity

generate_identity

Create fictional test identities with names, addresses, phone numbers, emails, jobs, and checksum-valid test cards for QA and demos.

Instructions

Generate a full fictional test identity (name, address, phone, email, job, test cards). For QA and demos only.

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": "generate_identity"
  }
}

Input Schema

NameRequiredDescriptionDefault
genderNorandom
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

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully flags that output is fictional and QA/demo-only, but it does not disclose that generation depends on an external service (fauxgen.com, visible only in the country parameter description), nor any rate limits, determinism, or repeat-call behavior.

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?

Two short sentences, zero filler, with the payload (what is produced) front-loaded and the usage constraint immediately after. Nothing could be removed without losing information.

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

Completeness4/5

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

For a no-annotation, no-output-schema tool, the description usefully enumerates the returned fields, which is exactly the information the absent output schema would otherwise provide. It omits only secondary context such as the external dependency and whether output is unique per call.

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 50%: country is richly documented in the schema while gender has no description. The description adds no parameter-level information at all, but the undocumented parameter is a self-explanatory enum with a default, so the schema gap is minor rather than critical.

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 and resource (generate a full fictional identity) and enumerates the sub-fields produced (name, address, phone, email, job, test cards), which implicitly separates it from the single-field siblings like generate_name and generate_email. It stops short of explicitly saying it is the composite alternative to those siblings.

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

Usage Guidelines3/5

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

'For QA and demos only' gives a clear exclusion (do not use for real data / production), which is genuine usage guidance. However, it never names the alternatives (the individual generators) or states when the composite is preferred over calling several single-field tools.

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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