The MCP Servers (OnePiece & Geolocalizar) provide two distinct functionalities:
OnePieceServer: Query One Piece character information by ID or retrieve a complete list of characters
Geolocalizar: Geolocate public IPv4 addresses to obtain country and location information
Both servers were developed with ModelContextProtocol SDK and can be executed via CLI or MCP Inspector.
Used to make HTTP requests to external APIs, enabling the MCP server to fetch One Piece character data and geolocation information for IP addresses.
Required runtime environment for the MCP server, with version 18 or higher needed.
Package manager used for installing dependencies, with version 9 or higher required.
The MCP server connects to a One Piece API hosted on Render (onepieceapi-50cm.onrender.com) to retrieve character information.
Provides validation for the geolocalizar tool to ensure inputs are valid IPv4 addresses.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Servers (OnePiece & Geolocalizar) find Luffy's character details"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
This project contains two MCP servers developed with @modelcontextprotocol/sdk . Each exposes a useful tool that can be integrated with an MCP-compatible AI client.
onePiece.ts: MCP server for querying One Piece characters
geolocalizar.ts: MCP server for geolocating public IP addresses
Related MCP server: MyAnimeList MCP Server
Node.js ≥ 18
npm ≥ 9
npm install @modelcontextprotocol/sdk axios zod
npm install -D tsxOnePieceServer allows you to view information about characters from the anime/manga One Piece, either individually or from the entire available list.
npx tsx onePiece.tsYou can also use the MCP Inspector:
npx -y @modelcontextprotocol/inspector npx -y tsx onePiece.tsone_pieceInput :
{ "id": "1" }For the complete list:
{ "id": "todos" }Output :
{
"content": [
{
"type": "text",
"text": "Información del personaje: { ... }"
}
]
}https://onepieceapi-50cm.onrender.com/personaje/{id}
https://onepieceapi-50cm.onrender.com/personajes
Geolocalizar allows you to obtain approximate geographic information from a public IP (IPv4) address.
npx tsx main.tsOr use with the MCP Inspector:
npx -y @modelcontextprotocol/inspector npx -y tsx main.tsgeolocalizarInput :
{ "ip": "8.8.8.8" }Output :
{
"content": [
{
"type": "text",
"text": "{ \"ip\": \"8.8.8.8\", \"country\": \"United States\", ... }"
}
]
}Use zod to validate that the input is a valid IP in IPv4 format.
.
├── geolocalizar.ts # MCP Geolocalizar
├── onePiece.ts # MCP OnePieceServer
├── package.json # Archivo de configuracion de NPM
└── README.md # Este archivoBoth servers communicate via stdin and stdout using StdioServerTransport , allowing easy execution from CLI or integration with MCP clients.
Developed by Diego Rodríguez
✉️ 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.
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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