RandomUser MCP Server
RandomUser MCP 서버
사용자 정의 서식, 비밀번호 생성, 가중 국적 분포와 같은 추가 기능을 통해 randomuser.me API에 대한 향상된 액세스를 제공하는 MCP 서버입니다.
설치
저장소를 복제합니다.
지엑스피1
Related MCP server: mcp-rando-server
용법
MCP 설정 파일( claude_desktop_config.json 또는 cline_mcp_settings.json )에 다음을 추가합니다.
{
"mcpServers": {
"randomuser": {
"command": "node",
"args": ["path/to/randomuserMCP/build/index.js"]
}
}
}사용 가능한 도구
무작위 사용자 가져오기
사용자 정의 옵션을 통해 무작위로 선택된 사용자를 얻으세요.
{
"gender": "female",
"nationality": "US",
"fields": {
"mode": "include",
"values": ["name", "email", "phone"]
},
"format": {
"type": "json",
"structure": {
"flattenObjects": true,
"nameFormat": "full"
}
},
"password": {
"charsets": ["special", "upper", "lower", "number"],
"minLength": 8,
"maxLength": 12
}
}여러 사용자 가져오기
가중치가 적용된 국적 분포를 바탕으로 여러 명의 무작위 사용자를 확보합니다.
{
"count": 10,
"nationality": ["US", "GB", "FR"],
"nationalityWeights": {
"US": 0.5,
"GB": 0.3,
"FR": 0.2
},
"fields": {
"mode": "include",
"values": ["name", "email", "nat"]
},
"format": {
"type": "csv",
"csv": {
"delimiter": ",",
"includeHeader": true
}
}
}출력 형식
서버는 다양한 출력 형식을 지원합니다.
JSON(기본값)
중첩되거나 평평한 객체
사용자 정의 가능한 이름 형식(전체, 이름_성, 구분)
날짜 형식 옵션(iso, unix, formatted)
CSV
사용자 정의 구분 기호
선택적 헤더
자동으로 평탄화된 데이터 구조
SQL
다양한 언어 지원(MySQL, PostgreSQL, SQLite)
선택적 CREATE TABLE 문
적절한 이스케이프 및 유형 처리
XML
표준 XML 형식
중첩된 데이터 구조
특수 문자의 적절한 이스케이프
필드 선택
특정 필드를 포함하거나 제외합니다.
{
"fields": {
"mode": "include", // or "exclude"
"values": [
"name",
"phone",
"email",
"location",
"picture",
"dob",
"login",
"registered",
"id",
"cell",
"nat"
]
}
}지원 국적
AU: 호주
BR: 브라질
CA: 캐나다
CH: 스위스
DE: 독일
DK: 덴마크
ES: 스페인
FI: 핀란드
FR: 프랑스
GB: 영국
IE: 아일랜드
IN: 인도
IR: 이란
MX: 멕시코
NL: 네덜란드
아니요: 노르웨이
NZ: 뉴질랜드
RS: 세르비아
TR: 터키
UA: 우크라이나
미국: 미국
개발
# Install dependencies
npm install
# Build the project
npm run build
# Start in development mode (with watch mode)
npm run dev
# Start the server
npm start특허
MIT
Available Tools
2 toolsget_multiple_usersC
Get multiple random users
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of users to generate | |
| gender | No | ||
| nationality | No | ||
| nationalityWeights | No | ||
| fields | No | ||
| format | No | ||
| password | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Get multiple random users' implies a read operation but doesn't specify whether this generates synthetic data, queries a database, or has side effects. It lacks critical behavioral context like rate limits, authentication needs, data freshness, or what 'random' entails (e.g., uniform distribution, seed control). The description is insufficient for a tool with 7 parameters and complex nested structures.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just three words, with zero wasted text. It's front-loaded and to the point, though this brevity comes at the cost of completeness. Every word ('Get', 'multiple', 'random', 'users') contributes directly to the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters with nested objects, 14% schema coverage, no output schema, and no annotations), the description is severely incomplete. It doesn't address what the tool returns, how 'random' generation works, the scope of user data, or the interplay between parameters like 'gender', 'nationality', and 'fields'. For a data generation tool with rich configuration options, this minimal description leaves critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 14%, meaning most parameters lack documentation in the schema. The description 'Get multiple random users' adds minimal semantic value—it only hints at the 'count' parameter for 'multiple' and 'random' which might relate to generation logic. It doesn't explain the purpose of complex parameters like 'nationalityWeights', 'fields', 'format', or 'password', leaving the agent to guess their roles from schema structure alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get multiple random users' states the basic action (get) and resource (users) with the qualifier 'multiple random', but it's vague about what 'random' means in this context and doesn't distinguish from the sibling tool 'get_random_user'. It provides a minimal purpose statement without specificity about the source or nature of these users.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. There's no mention of the sibling tool 'get_random_user', nor any context about appropriate use cases, prerequisites, or constraints. The agent must infer usage solely from the tool name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_random_userC
Get a single random user
| Name | Required | Description | Default |
|---|---|---|---|
| gender | No | Filter results by gender | |
| nationality | No | Specify nationality | |
| fields | No | Specify which fields to include | |
| format | No | ||
| password | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Get a single random user' implies a read operation but doesn't address important behavioral aspects like rate limits, authentication requirements, data freshness, or what 'random' means in practice (uniform distribution, seed behavior, etc.). The description is too minimal for a tool with 5 parameters and complex nested structures.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 5 words, with no wasted language. It's front-loaded with the core purpose and uses minimal syntax. While potentially under-specified, it earns full marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 parameters with nested objects, no output schema, no annotations), the description is severely incomplete. It doesn't explain the tool's behavior, parameter usage, return format, or relationship to sibling tools. For a tool with this level of parameter complexity, the minimal description fails to provide adequate context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions no parameters at all, despite the input schema having 5 parameters with only 60% description coverage. The schema documents gender, nationality, fields, format, and password parameters with varying detail, but the description adds zero semantic context about what these parameters do or how they affect the random user generation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('a single random user'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'get_multiple_users' beyond the 'single' vs 'multiple' distinction, which is implied but not explicitly stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 its sibling 'get_multiple_users' or any alternatives. There's no mention of use cases, prerequisites, or trade-offs between getting a single random user versus multiple users.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
get_multiple_users - First observed
get_random_user
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one retrieves a single random user, while the other retrieves multiple random users. There is no overlap or ambiguity in their functions, making it easy for an agent to select the appropriate tool based on the desired outcome.
Both tool names follow a consistent verb_noun pattern with 'get' as the verb and descriptive nouns ('random_user', 'multiple_users'). The naming is uniform and predictable, using snake_case throughout without any deviations.
With only 2 tools, the server feels thin for a 'RandomUser' domain, as it lacks operations like filtering users by criteria, updating user data, or handling user-related workflows. While the tools cover basic retrieval, the count is too low for a comprehensive user management or data generation scope.
The tool surface is severely incomplete for a user-related server, offering only retrieval of random users without any ability to create, update, delete, or filter users. There are significant gaps that would limit agent functionality, such as no way to specify user attributes or manage user data beyond basic fetching.
Maintenance
Related MCP Connectors
Random User MCP — wraps randomuser.me (free, no auth)
Generate synthetic random user data for testing, demos, and development without using real persona.
Harness the power of names with our Name Demographics MCP. Using Agify, Genderize, and Nationalize
Disify MCP — wraps the Disify API (anonymous tier + BYO key)
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