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KinielaGPT MCP Server

@RicardoMoya

Repository

Basic information

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Other

Last updated

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Author

RicardoMoya

Submitted by

Ricardo Moya Garcia

About KinielaGPT MCP Server

KinielaGPT es un servidor MCP (Model Context Protocol) diseñado para potenciar tus predicciones de la Quiniela mediante un análisis avanzado de datos. Combina las probabilidades oficiales de LAE con un análisis contextual profundo: histórico de enfrentamientos, rachas recientes,

#quiniela#f-tbol#football#predicci-n#prediction#machine-learning#an-lisis-deportivo#sports-analytics#la-liga#soccer

KinielaGPT MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "kinielagpt": {
      "command": "python",
      "args": [
        "-m",
        "kinielagpt"
      ]
    }
  }
}

KinielaGPT MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is KinielaGPT?

KinielaGPT is an MCP server for predicting the Spanish football pool (La Quiniela) by combining official LAE probabilities with contextual analysis such as historical matchups, recent streaks, league standings, and home/away performance. It is aimed at users who want data‑driven predictions and deeper match insights.

How to use KinielaGPT?

After configuring the MCP server, interact with any LLM (Claude, GPT, Gemini, etc.) in natural language. For example, ask about the latest jornada, request a conservative/risky/custom prediction, analyze a specific match, or detect possible surprises. The server exposes 7 specialized tools usable from Claude Desktop, VS Code, and other MCP clients.

Key features of KinielaGPT

  • Three prediction strategies: conservative, risky, and custom.
  • Integrates LAE probabilities, 10‑year historical duels, streaks, standings, and context.
  • Surprise detection by comparing official odds with actual performance.
  • Detailed team form: recent scores, streaks, home/away performance.
  • Access both interpreted analysis and raw data.
  • 7 native MCP tools, compatible with major MCP clients.

Use cases of KinelaGPT

  • Generate a conservative quiniela for the current matchday.
  • Analyze a specific match (e.g., Real Madrid vs. opponent) with full context.
  • Detect potential surprises in a jornada using a configurable threshold.
  • Examine a team’s recent form, streaks, and trends.
  • Retrieve historical head‑to‑head records for any pairing.

Frequently asked questions

1

What data does KinielaGPT use for predictions?

It uses official LAE probabilities, historical matchups (last 10 years), recent streaks, league standings, and home/away performance data.

2

What are the runtime requirements?

Python 3.10 or higher. The server is MCP‑compatible and licensed under AGPL v3.

3

Which clients support KinielaGPT?

Claude Desktop, VS Code, and any client that supports the Model Context Protocol (MCP).

4

Does KinielaGPT require an internet connection?

The README does not explicitly state this, but fetching LAE probabilities and historical data likely requires an active connection.

5

What prediction strategies are available?

Three: conservative (max probability), risky (balance probability and context), and custom (specify counts of 1, X, and 2).

Comments

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