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Hackathonwatch MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-hackathonwatch": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "A JSON string containing the configuration",
        "SECURITY": "Environment variables for security parameters (e.g., API keys)",
        "CONFIG_PATH": "Path to a JSON configuration file (e.g., mcp_server/mcp_config.json)"
      }
    }
  }
}

You run an MCP (Model Context Protocol) Server that exposes the OpenAPI-driven capabilities of hackathonwatch, enabling you to connect from an MCP client and request data or actions described by the API. This server is designed for local or embedded use, and it can operate in a standard input/output (stdio) transport, making it easy to integrate into scripts, test harnesses, or development environments.

How to use

Start the MCP server in stdio mode to enable seamless integration with your tooling. You will launch a single command that keeps the server running and communicates via standard input and output. Use your MCP client to connect, send requests, and receive responses according to the MCP protocol. You can also supply configuration through environment variables or a JSON string to customize behavior and security.

How to install

Prerequisites you need on your system:

Python 3.9+ must be installed on the host system

Install tooling for development and testing

pip and uv should be available in your Python environment

Step by step commands

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

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

# Alternative (using uv if you prefer)
uv pip install --editable ".[dev]"

Additional content

Configuration and runtime options are available to tailor security and file locations. The server accepts configuration via a JSON file path or a JSON string, and you can set security-related environment variables as needed. Typical environment variables you may use include CONFIG_PATH, CONFIG, and SECURITY. The server entry point is designed to be invoked with a transport mode of stdio and will read these values at startup.

Example startup consideration: place your configuration in mcp_server/mcp_config.json and start the server with the stdio transport as described in the next section.

Available tools

Linting and formatting

Ruff is used for linting and formatting the codebase to maintain style and quality.

Static analysis

Static analysis tools such as mypy, bandit, and semgrep are used to check type safety and security.

Testing

pytest is used to run the test suite and generate coverage reports.

Pre-commit hooks

Pre-commit hooks are configured to run checks before each commit.

Build and publish tooling

Hatch is used for building and publishing the project.