football-scraper-mcp

football-scraper-mcp

Provides tools to query football match data, odds, standings, and team statistics via natural language, integrating with the football-scraper-api.

Category
访问服务器

README

Football Scraper MCP Server

A Model Context Protocol (MCP) server that provides access to football match data, odds, and standings from the football-scraper-api.

Overview

This MCP server exposes tools for querying football data including:

  • Live matches and scores
  • Today's and upcoming matches
  • Match details and betting odds
  • League standings and tables
  • Team statistics and head-to-head records
  • API health and statistics

Prerequisites

Installation

1. Clone and navigate to the MCP server directory

cd football-scraper-mcp

2. Install dependencies

Option A: Using virtual environment (recommended)

If you have python3-venv installed:

python3 -m venv venv
source venv/bin/activate
pip install -e .

If you don't have python3-venv, install it first:

sudo apt install python3-venv

Option B: System-wide installation

On Debian/Ubuntu systems with externally managed Python:

pip3 install -e . --break-system-packages

Or if you have modified your pip configuration:

pip3 install -e .

4. Configure environment variables

cp .env.example .env

Edit .env to set your API base URL:

API_BASE_URL=http://localhost:3000/api/v1

Usage

Running the server directly

If using virtual environment:

source venv/bin/activate
python3 src/server.py

Or with the full path:

./venv/bin/python3 src/server.py

If using pipx:

football-scraper-mcp

If installed system-wide:

python3 src/server.py

Running with MCP CLI

python3 -m mcp run src/server.py

Docker

Build and run with Docker:

docker build -t football-scraper-mcp .
docker run -i --rm -e API_BASE_URL=http://host.docker.internal:3000/api/v1 football-scraper-mcp

Available Tools

Match Tools

Tool Description
get_live_matches Get all currently live football matches
get_today_matches Get all matches scheduled for today
get_matches Get matches with flexible filtering (league, status, date, etc.)
search_matches Search matches by team name
get_match_by_id Get detailed information about a specific match
get_match_odds Get betting odds for a specific match
get_head_to_head Get historical matches between two teams

League Tools

Tool Description
get_leagues Get all supported leagues
get_league_by_id Get detailed information about a specific league

Standings Tools

Tool Description
get_standings Get standings for all leagues
get_league_standings Get standings for a specific league
get_team_standing Get standing information for a specific team

Statistics Tools

Tool Description
get_stats Get comprehensive statistics about matches in the database
get_health Get API health status and system information
get_health_stats Get detailed scraping statistics for the last 24 hours

MCP Configuration

Add this server to your MCP settings (e.g., in Claude Desktop or other MCP clients):

Claude Desktop Configuration

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%/Claude/claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "football-scraper": {
      "command": "/path/to/football-scraper-mcp/venv/bin/python3",
      "args": ["/path/to/football-scraper-mcp/src/server.py"],
      "env": {
        "API_BASE_URL": "http://localhost:3000/api/v1"
      }
    }
  }
}

Using with Docker

{
  "mcpServers": {
    "football-scraper": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "API_BASE_URL=http://host.docker.internal:3000/api/v1",
        "football-scraper-mcp"
      ]
    }
  }
}

Example Queries

Once configured, you can ask your AI assistant questions like:

  • "What football matches are live right now?"
  • "Show me today's Premier League matches"
  • "Get the standings for La Liga"
  • "What are the odds for the Manchester City vs Arsenal match?"
  • "Show me the head-to-head history between Real Madrid and Barcelona"
  • "Search for matches involving Liverpool"
  • "Get all matches from the Champions League"

API Reference

This MCP server connects to the football-scraper-api. See the main API README for detailed endpoint documentation.

Development

Project Structure

football-scraper-mcp/
├── src/
│   └── server.py          # Main MCP server implementation
├── pyproject.toml         # Python dependencies
├── Dockerfile             # Container configuration
├── .env.example           # Environment template
├── .gitignore            # Git ignore rules
└── README.md             # This file

Adding New Tools

To add a new tool, define a new async function with the @mcp.tool() decorator:

@mcp.tool()
async def my_new_tool(param: str) -> str:
    """Description of what this tool does.
    
    Args:
        param: Description of the parameter
    
    Returns:
        Description of the return value
    """
    return await make_api_request("/endpoint", {"param": param})

License

MIT

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选