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FauxGen MCP

FauxGen MCP

by LazyInvestor
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Generate fake emails

generate_email

Create one or more fictional email addresses to seed test users, demos, or QA data without exposing real inboxes.

Instructions

Generate one or more fictional email addresses.

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_email"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNo

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. 'Fictional' usefully signals no real deliverable address, but it says nothing about whether domains are real-looking, whether addresses are unique across calls, or any rate/volume behavior beyond the schema's max of 50.

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 sentence with the verb and resource front-loaded and no filler. It is appropriately sized for a trivial generator, though it is minimal to the point of leaving gaps.

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 one-parameter fake-data generator with no output schema, the description covers the essentials but omits output shape (what a generated address looks like, whether a domain is included). Given the tool's simplicity this is adequate but not complete.

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 0% and the single 'count' parameter is undocumented in the schema. The phrase 'one or more' partially compensates by implying the count parameter controls quantity, but no default or upper bound is explained in prose.

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?

Specific verb 'generate' plus resource 'email addresses', and the cardinality ('one or more') is stated. The sibling set is entirely distinct resources (name, address, phone, username), so the resource alone differentiates it, though the description never explicitly contrasts with generate_username, which is the closest neighbor.

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 guidance, no exclusions, and no mention of the sibling tools an agent might confuse it with. The word 'fictional' hints at the intended use case (test data), but that is inference rather than stated guidance.

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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