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MCP Server generated by mcp.ag2.ai
Configuration
View docs{
"mcpServers": {
"ag2-mcp-servers-gke-hub-api": {
"command": "python",
"args": [
"mcp_server/main.py",
"stdio"
],
"env": {
"CONFIG": "JSON string containing the configuration",
"SECURITY": "Security parameters such as API keys",
"CONFIG_PATH": "Path to a JSON configuration file (e.g., mcp_server/mcp_config.json)"
}
}
}
}This MCP server hosts the Model Context Protocol interface for the Google Kubernetes Engine Hub v1beta1 API, enabling client applications to interact with the API through a standardized MCP channel. It supports local execution and can be integrated into your development or deployment workflows to provide consistent MCP-based access to the GKE Hub data and actions.
You will run this MCP server locally (or in your environment) and connect an MCP client to it using the stdio transport. The server exposes a structured MCP interface for the GKE Hub API, allowing you to request data, trigger actions, and observe changes through MCP-compatible tooling. Use your MCP client to start conversations, fetch resources, and send commands through the same lifecycle you use for other MCP servers.
Prerequisites: Python 3.9+ and a working Python toolchain (pip and uv).
1. Clone the repository.
git clone <repository-url>
2. Change into the project directory.
cd mcp-server
3. Install dependencies.
The development setup uses a script to install dependencies with pip in editable mode.
pip install -e ".[dev]"
Alternatively, you can use uv to install dependencies in editable mode.
uv pip install --editable ".[dev]"
4. Run the server in stdio mode.
python mcp_server/main.py stdioYou can configure the server using environment variables. The following are supported:
- CONFIG_PATH: Path to a JSON configuration file (for example, mcp_server/mcp_config.json).
- CONFIG: A JSON string containing the configuration.
- SECURITY: Environment variables for security parameters (for example, API keys).