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Cloud DNS MCP Server

MCP Server generated by mcp.ag2.ai

Installation

Add the following to your MCP client configuration file.

Configuration

{
  "mcpServers": {
    "ag2-mcp-servers-cloud-dns-api": {
      "command": "python",
      "args": [
        "mcp_server/main.py",
        "stdio"
      ],
      "env": {
        "CONFIG": "{\"example\":\"config\"}",
        "SECURITY": "YOUR_SECURITY_PARAMS",
        "CONFIG_PATH": "PATH_TO_CONFIG.json"
      }
    }
  }
}

You can run a dedicated MCP (Model Context Protocol) server that exposes the Google DNS v2 API as an MCP endpoint. It lets you connect an MCP client to the DNS API through a configurable, language-native server bridge, enabling consistent data access and actions within your development or integration workflow.

How to use

Start the local MCP server in stdio mode to run as a lightweight, self-contained process. Use your MCP client to connect to the server and perform operations against the DNS v2 API through the MCP interface. You can stop the server at any time and restart it as part of your development cycle.

How to install

Prerequisites before installation include Python 3.9 or newer, and the ability to run Python and package managers on your system.

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

# 2) Install dependencies
pip install -e ".[dev]"
# If you prefer to use uv to run development tasks:
# uv pip install --editable ".[dev]"

# 3) Optional: run static checks and tests (see Development section for details)

Additional notes

Configuration is driven by environment variables at runtime. The following variables influence how the server runs and where it looks for its configuration.

{
  "CONFIG_PATH": "Path to a JSON configuration file (e.g., mcp_server/mcp_config.json)",
  "CONFIG": "A JSON string containing the configuration",
  "SECURITY": "Environment variables for security parameters (e.g., API keys)"
}

Available tools

lint

Run linting to ensure code quality and consistency across the repository.

format

Format code according to project standards to maintain readability and reduce diffs.

static_analysis

Perform static analysis (type checking, security checks, etc.) to catch issues early.

tests

Execute the test suite and collect coverage to verify behavior and prevent regressions.