Skip to main content
Glama
deenesjakoruzh
parrotsoft

Lotería MCP

by parrotsoft
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

🎟️ Lotería MCP

Lottery Results API を使用して宝くじや結果を照会するための MCP サーバーです。

互換性のある MCP クライアント（Claude Desktop、Cursor など）がチャットから直接呼び出せる 2 つのツールを提供します。

📋 要件

ツール

最小バージョン

Python

3.10+

uv

latest

Related MCP server: Marvel MCP

⚙️ インストール

1. リポジトリのクローン

git clone https://github.com/parrotsoft/loteria-mcp
cd loteria

2. 仮想環境の作成と uv を使用した依存関係のインストール

uv sync

これにより、.venv 環境が自動的に作成され、pyproject.toml で宣言されたすべての依存関係がインストールされます。

🚀 Claude Desktop での使用方法

Claude Desktop の設定ファイルに以下の設定を追加します：

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "loteria": {
      "command": "uv",
      "args": [
        "--directory",
        "/ruta/absoluta/al/proyecto/loteria",
        "run",
        "loteria.py"
      ]
    }
  }
}

注: /ruta/absoluta/al/proyecto/loteria は、お使いの環境の実際のプロジェクトパスに置き換えてください。

Claude Desktop を再起動すると、サーバーが利用可能になります。

🛠️ 利用可能なツール

get_lotteries

API で利用可能な宝くじの全リストを返します。

パラメータなし。

レスポンス例:

{
  "data": [
    { "id": 1, "name": "Lotería Nacional", "country": "MX" },
    { "id": 2, "name": "Melate", "country": "MX" }
  ]
}

get_resultados

特定の日の宝くじ結果を返します。

パラメータ

型

説明

date

str

YYYY-MM-DD 形式の日付。空の場合は最新の結果

レスポンス例:

{
  "data": [
    { "lottery": "Lotería Nacional", "result": "1234", "date": "2026-04-24" }
  ]
}

🧪 開発モードでの実行

ターミナルから直接サーバーをテストするには：

uv run mcp dev loteria.py

これによりブラウザで MCP Inspector が開き、対話的にツールを呼び出すことができます。

📦 依存関係

パッケージ

説明

httpx

API 呼び出し用の非同期 HTTP クライアント

mcp[cli]

Model Context Protocol フレームワーク

📁 プロジェクト構造

loteria/
├── loteria.py        # Servidor MCP con las herramientas expuestas
├── main.py           # Punto de entrada alternativo
├── pyproject.toml    # Configuración del proyecto y dependencias
├── uv.lock           # Lock file de dependencias (uv)
├── .gitignore
└── README.md

📄 ライセンス

MIT

Available Tools

2 tools
get_lotteriesA

Obtiene el listado de todas las loterías disponibles.

Consulta el endpoint `/lotteries` de la API de resultados de loterías
y retorna la información de cada lotería registrada (nombre, país, etc.).

Returns:
    dict[str, Any] | None: Diccionario con la lista de loterías disponibles,
    o None si ocurre un error de red o la API no responde.

Example:
    >>> await get_lotteries()
    {"data": [{"id": 1, "name": "Lotería Nacional", ...}, ...]}
ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explicitly states the tool returns a dict or None on network error, and that it queries an API. It does not mention auth or rate limits, but for a read-only list tool, this is adequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with three parts: purpose, endpoint, and return type with example. Each sentence adds value without redundancy, making it well-structured and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity, no parameters, and existence of an output schema, the description fully suffices. It explains the return structure and includes an example, meeting completeness requirements.

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

Parameters4/5

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

The input schema has no parameters, and schema coverage is 100%. Per the guidelines, a baseline of 4 is assigned for zero parameters, and the description adds no further parameter info, which is appropriate.

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 clearly states it obtains the list of all available lotteries by querying the /lotteries endpoint, providing specific verb and resource. The sibling tool 'get_resultados' is for results, so this tool is distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. Usage is implied by the tool's purpose but not articulated.

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

get_resultadosA

Obtiene los resultados de loterías para una fecha específica.

Consulta el endpoint `/results/{date}` de la API cuando se proporciona
una fecha, o `/results` para obtener los resultados más recientes.

Args:
    date (str): Fecha en formato `YYYY-MM-DD` para filtrar los resultados.
        Si se pasa una cadena vacía, retorna los resultados más recientes.

Returns:
    dict[str, Any] | None: Diccionario con los resultados de loterías
    para la fecha indicada, o None si ocurre un error de red o la API
    no responde.

Example:
    >>> await get_resultados("2026-04-24")
    {"data": [{"lottery": "Lotería Nacional", "result": "1234", ...}]}
ParametersJSON Schema
NameRequiredDescriptionDefault
dateYes

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description fully carries the burden. It explains that it queries an API endpoint, returns a dict or None on network error, and includes an example. This is adequate disclosure of behavior.

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?

Description is structured in sections (Args, Returns, Example) and front-loaded. It is slightly verbose but still efficient for the information provided.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (1 param, output schema present), the description covers purpose, parameter semantics, return type, and error cases. It does not mention the sibling tool, but completeness is acceptable.

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

Parameters5/5

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

Schema coverage is 0%, but the description contains an extensive 'Args' section explaining the single parameter 'date'—format, behavior when empty, and example. It adds significant meaning beyond the schema.

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?

The description clearly states the tool obtains lottery results for a specific date ('Obtiene los resultados de loterías para una fecha específica'). It distinguishes from the sibling tool 'get_lotteries' which likely lists lotteries, but does not explicitly contrast them.

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 guidance on when to use this tool instead of the sibling 'get_lotteries'. The description provides parameter usage (empty string for most recent) but not tool selection context.

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.

  1. 2 tool updatesv0.1.0
    • First observedget_lotteries
    • First observedget_resultados
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4/5.0

Scored across 2 tools

Disambiguation5/5

The two tools have clearly distinct purposes: one lists all available lotteries, the other retrieves results for a specific date. There is no risk of confusion.

Naming Consistency5/5

Both tools follow a consistent 'get_<resource>' pattern in snake_case, using the same language (Spanish) throughout.

Tool Count3/5

Two tools is minimal but reasonable for a simple read-only lottery information server. It borders on feeling thin but does not warrant a lower score.

Completeness3/5

The server covers listing lotteries and fetching results by date, but lacks features like filtering by lottery or retrieving historical results beyond a single date.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers