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Soccer V3 Scores MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-soccer-v3-scores": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "<CONFIG>",
        "SECURITY": "<SECURITY>",
        "CONFIG_PATH": "<CONFIG_PATH>"
      }
    }
  }
}

You run an MCP server that exposes a defined model/context protocol for soccer data scores. This server lets MCP clients query and interact with the soccer data API in a structured, consistent way, enabling you to build tooling and integrations without dealing with the underlying API directly.

How to use

Start the server in a local development mode so MCP clients can connect through a standard transport. The server supports multiple transport modes, including stdio, sse, and streamable-http. In typical development you run it in stdio mode to interact directly from scripts or test harnesses.

Once the server is running, you can configure clients to connect using the stdio transport by invoking the Python command shown in the installation steps. Your MCP client will issue requests in the MCP format and receive responses that align with the Soccer V3 Scores data model.

How to install

# Prerequisites
python3.9+
pip install uv

# 1) Clone the project
git clone <repository-url>
cd mcp-server

# 2) Install dependencies (dev setup)
pip install -e ".[dev]"

# Alternative using uv for editable install
uv pip install --editable ".[dev]"

### Run the server in stdio mode To start the server in stdio mode, run the following command. This uses the local Python runtime to execute the MCP server entry point.

python mcp_server/main.py stdio

Additional sections

Configuration and runtime behavior are controlled through environment variables. The following variables are recognized and can be used to tailor your MCP server instance.

- CONFIG_PATH: Path to a JSON configuration file (for example, mcp_server/mcp_config.json).

- CONFIG: A JSON string containing the configuration directly.

- SECURITY: Environment variables for security parameters (such as API keys).

Notes on building, testing, and tooling

The project uses several tools for quality and reliability. Use them to keep the codebase healthy and ensure your MCP server behaves as expected.

Linting and formatting are handled by a Python tooling suite. Static type checking helps catch type errors early, and tests verify server behavior.

Troubleshooting and tips

If you encounter issues starting the server, check that Python 3.9+ is installed and that you can access the mcp_server/main.py script. Verify that the environment variables CONFIG_PATH, CONFIG, and SECURITY are set if you rely on file-based or JSON-string configurations.

Available tools

start_server

Launch the MCP server using the standard Python command to start the process in stdio mode.

lint

Run code linting to ensure style and error checks during development.

format

Format codebase to adhere to style guidelines.

static_analysis

Run static analysis tools like mypy, bandit, and semgrep to validate type safety and security.

run_tests

Execute the test suite to verify functionality and generate coverage reports.