About ⚽️ Soccerdata MCP Server
Soccerdata MCP Server is an open-source MCP server that uses the SoccerDataAPI to deliver live football match information through natural language queries. It is aimed at users of MCP clients such as Claude Desktop who want football data.
Key features
- 01Live match listings and basic details
- 02Match details and key events
- 03Starting lineups and bench players
- 04Odds and handicap betting information
- 05League metadata
Use cases
- 01Asking an AI client for scores of matches in progress
- 02Checking predicted lineups for upcoming matches
- 03Reviewing goals and events from recently finished matches
MCP support
This project is an MCP server that exposes a single get_livescores tool, which returns real-time information about ongoing matches worldwide.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README⚽️ Soccerdata MCP Server
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MCP-Soccerdata is an open-source Model Context Protocol (MCP) server that connects to the SoccerDataAPI to deliver up-to-date football match information via natural language interactions.
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Designed for use with MCP-enabled clients such as Claude Desktop, it allows users to retrieve football data by leveraging large language models (LLMs).
✨ Features
🏟️ Live Football Match Insights
MCP-Soccerdata focuses on delivering real-time information about ongoing football matches around the world.
"What football matches are being played right now?"
"What are the predicted lineups for PSG vs Aston Villa today?"
"Please tell me the scores and number of goals from recent football matches."
→ Provides relevant football data in a structured format, including the detailed categories described below.
- Match Listings & Basic Info
- Global list of all currently active matches
- Home and away team names
- Kickoff time and match date
- Stadium details
- Current score
- Match Details
- Match status: scheduled, in progress, or finished
- Goal breakdown: first half, second half, extra time, penalty shootout
- Final result: win, draw, or loss
- Key Match Events
- Goal events (who scored, when, how)
- Substitutions
- Yellow and red cards
- Penalties
- Team Lineups
- Starting XI
- Bench players
- Injury status
- Team formation
- Odds & Betting Information
- Win / Draw / Lose odds
- Over / Under odds
- Handicap betting odds
- League Metadata
- League name
- Country
- Competition format (e.g., regular season, knockout stage)
⚠️ Focused exclusively on live, upcoming, and recently finished matches
🎥 Demo
🚀 Quick Start
Installing via Smithery
To install Amadeus MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @yeonupark/mcp-soccer-data --client claude
Prerequisites
- Python 3.12+
uvpackage manager- Soccerdata API account
- MCP-compatible client (e.g., Claude for Desktop)
1. Clone and Setup
- Clone the repository
git clone https://github.com/yeonupark/mcp-soccer-data.git
cd mcp-soccer-data
- Install dependencies
uv sync
2. Get Your API Key and Set Environment
- Create a .env file with your credentials:
AUTH_KEY=your_auth_key
Sign up on https://soccerdataapi.com/ and get your own Auth keys.
3. Configure MCP Client
- Register this server in your MCP client (e.g., Claude for Desktop).
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"mcp-soccer-data": {
"command": "/ABSOLUTE/PATH/TO/PARENT/FOLDER/uv",
"args": [
"--directory",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/src/",
"run",
"--env-file",
"/ABSOLUTE/PATH/TO/PARENT/FOLDER/.env",
"server.py"
]
}
}
}
🛠️ Tools
The follwing tool is exposed to MCP clients:
get_livescores()
-> Returns real-time information about ongoing football matches around the world.
📝 License
- This project is licensed under the MIT License. See the LICENSE file for details.
- Built with Model Context Protocol
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
