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Groundhog Day MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-groundhog-day-api": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "{...}",
        "SECURITY": "YOUR_API_KEY",
        "CONFIG_PATH": "mcp_server/mcp_config.json"
      }
    }
  }
}

You run an MCP (Model Context Protocol) Server that exposes a defined OpenAPI spec to MCP clients. It enables you to query, update, and reason about model context data through a consistent, protocol-driven interface, with transport options that fit your workflow. This guide shows how to install, configure, and run the server so your clients can connect and exchange contextual data efficiently.

How to use

Start the MCP server in stdio mode to establish a local interface that MCP clients can talk to through standard input and output. Connect using your client’s MCP workflow, select the stdio transport, and point the client at the running process. You can also explore other transport modes such as sse or streamable-http if your client supports them.

How to install

Prerequisites include Python 3.9 or newer, plus pip and the uv tool for optional editable installs.

1. Clone the repository.

git clone <repository-url>
cd mcp-server

2. Install development dependencies. Use the following command to install in editable mode with dev dependencies.

pip install -e ".[dev]"

Alternatively, you can install dependencies using uv for an editable setup.

uv pip install --editable ".[dev]"

Running the server and environment configuration

To start the MCP server in stdio mode, run the following command.

python mcp_server/main.py stdio

You can configure the server using environment variables shown here.

CONFIG_PATH points to a JSON configuration file, CONFIG contains a JSON string with the configuration, and SECURITY holds security-related parameters such as API keys.

CONFIG_PATH=mcp_server/mcp_config.json
CONFIG='{"server":"example"}'
SECURITY={"apiKey":"YOUR_API_KEY"}

Troubleshooting and tips

If you need to run static checks, linting, or tests, you can rely on the standard tooling to keep the codebase healthy. Refer to the script shortcuts in the project for detailed commands.

Available tools

Linting

Run linting with ruff to ensure code style and quality.

Formatting

Format code with ruff to maintain consistent style.

Static analysis

Run static analysis tools (mypy, bandit, semgrep) to detect type issues and security concerns.

Testing

Execute tests with pytest and generate coverage reports to validate changes.

Pre-commit

Use pre-commit hooks to catch issues before commits.

Server run

Start the MCP server in a chosen transport mode (stdio, sse, streamable-http).