naija-faker-mcp

Generate a fake name

generate_name

Read-only

Create synthetic Nigerian names by selecting gender and language (Hausa, Igbo, Yoruba) to generate realistic test data.

Instructions

Generates a synthetic Nigerian name.

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_name"
  }
}

Input Schema

Name	Required	Description	Default
`gender`	No
`language`	No

Output Schema

Name	Required	Description	Default
`value`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 schema fields changedv2.0.0Sep 16, 2026

removedInput schema / properties / gender / description

Removed value: -"The gender of the name data. The accepted gender values are male and female"

addedInput schema / properties / gender / enum
```
Added value: +[
+  "male",
+  "female"
+]
```

removedInput schema / properties / language / description

Removed value: -"The language of the name data. The available languages are Hausa, Igbo and Yoruba"

addedInput schema / properties / language / enum

Added value: +[
+  "hausa",
+  "igbo",
+  "yoruba"
+]

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "value": {}
+  },
+  "required": [
+    "value"
+  ],
+  "type": "object"
+}

First observedv1.0.1Sep 13, 2026

TDQS

B3.2/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds 'synthetic', indicating the name is fake, but it does not disclose whether the generated name is random, independent across calls, or consistent—an important distinction given the generate_consistent_person siblings.

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 single sentence with no fluff, front-loading the verb. It is appropriately short, though it is concise to the point of under-specification because it omits behavioral and parameter context.

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?

Given the large sibling family including generate_person, generate_consistent_person, and generate_title, the description is not complete enough for an agent to reliably choose this tool. The output schema may cover return shape, but the description does not provide the behavioral or routing context needed to fully disambiguate it.

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

Parameters2/5

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

Schema description coverage is 0%, and the description never mentions the gender or language parameters. The 'Nigerian' qualifier hints that the language enum values correspond to Nigerian languages, but the agent must infer all parameter meaning from the enum labels alone. No defaults, optionality, or combination behavior are described.

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

Purpose5/5

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

The description uses a specific verb, 'Generates', and a specific resource, 'synthetic Nigerian name', which clearly distinguishes it from sibling tools like generate_person, generate_people, and generate_title. The 'Nigerian' qualifier narrows the scope further and makes the tool's purpose immediately recognizable.

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?

There is no guidance on when to use this tool versus alternatives such as generate_person, generate_consistent_person, or generate_title. The description does not state whether this is appropriate for standalone random names, consistent names, or full person objects, leaving the agent to guess.

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