이 프로젝트에는 @modelcontextprotocol/sdk 로 개발된 두 개의 MCP 서버가 포함되어 있습니다. 각각은 MCP 호환 AI 클라이언트에 통합될 수 있는 유용한 도구를 제공합니다.
onePiece.ts: 원피스 캐릭터 쿼리를 위한 MCP 서버
geolocalizar.ts: 공용 IP 주소를 지리적으로 찾기 위한 MCP 서버
Related MCP server: MyAnimeList MCP Server
노드.js ≥ 18
npm ≥ 9
지엑스피1
OnePieceServer 이용하면 애니메이션/만화 원피스의 캐릭터에 대한 정보를 개별적으로 또는 사용 가능한 전체 목록에서 볼 수 있습니다.
npx tsx onePiece.tsMCP 검사기를 사용할 수도 있습니다.
npx -y @modelcontextprotocol/inspector npx -y tsx onePiece.tsone_piece입력 :
{ "id": "1" }전체 목록은 다음과 같습니다.
{ "id": "todos" }출력 :
{
"content": [
{
"type": "text",
"text": "Información del personaje: { ... }"
}
]
}https://onepieceapi-50cm.onrender.com/personaje/{id}
https://onepieceapi-50cm.onrender.com/personajes
Geolocalizar 이용하면 공용 IP(IPv4) 주소에서 대략적인 지리적 정보를 얻을 수 있습니다.
npx tsx main.ts또는 MCP Inspector와 함께 사용하세요.
npx -y @modelcontextprotocol/inspector npx -y tsx main.tsgeolocalizar입력 :
{ "ip": "8.8.8.8" }출력 :
{
"content": [
{
"type": "text",
"text": "{ \"ip\": \"8.8.8.8\", \"country\": \"United States\", ... }"
}
]
}zod 사용하여 입력이 IPv4 형식의 유효한 IP인지 확인합니다.
.
├── geolocalizar.ts # MCP Geolocalizar
├── onePiece.ts # MCP OnePieceServer
├── package.json # Archivo de configuracion de NPM
└── README.md # Este archivo두 서버는 StdioServerTransport 사용하여 stdin 및 stdout 으로 통신하므로 CLI에서 쉽게 실행하거나 MCP 클라이언트와 통합할 수 있습니다.
Diego Rodríguez 가 개발
✉️ contacto@diegorodriguez.dev
Herramienta para buscar informacion sobre personajes de One Piece
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Id del personaje |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states what the tool does (search for character information) but doesn't reveal any behavioral traits such as whether it's read-only or mutative, what format the information returns in, error conditions, rate limits, or authentication requirements. This leaves significant gaps in understanding how the tool behaves.
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 a single, clear sentence in Spanish that directly states the tool's purpose without any unnecessary words. It's appropriately sized and front-loaded, making it easy for an agent to quickly understand the core functionality.
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 that there are no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of information is returned (e.g., character details, biography, abilities), the format of the response, or any error handling. For a search tool with no structured output documentation, the description should provide more context about the results.
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 input schema has 100% description coverage (the 'id' parameter is documented as 'Id del personaje'), so the baseline score is 3. The description doesn't add any additional meaning about the parameter beyond what the schema already provides—it doesn't explain what constitutes a valid character ID, provide examples, or clarify the search scope.
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 tool's purpose: 'buscar informacion sobre personajes de One Piece' (search for information about One Piece characters). It specifies both the verb (search) and resource (One Piece characters). However, since there are no sibling tools mentioned, we cannot assess differentiation from alternatives, so it cannot achieve a perfect 5.
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. It doesn't mention any prerequisites, constraints, or contextual factors that would help an agent decide when this tool is appropriate. The absence of sibling tools means there's no explicit comparison, but the description still lacks basic usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
one_pieceScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a clear, distinct purpose focused on searching One Piece character information.
With only one tool, naming consistency is inherently perfect. The tool name 'one_piece' follows a clear snake_case pattern and directly reflects its domain, though there is no pattern to evaluate across multiple tools.
The server has only one tool, which is too few for its apparent scope covering both One Piece and Geolocalizar domains. This minimal toolset severely limits functionality and suggests an incomplete implementation for the server's stated purpose.
The tool surface is severely incomplete. The server name suggests coverage of both One Piece and Geolocalizar domains, but only provides a single tool for One Piece character search, with no tools for Geolocalizar and no CRUD/lifecycle operations for either domain.
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