iflow-mcp_sbarbett-pihole-mcp-server

# 🍓 pihole-mcp-serer A Model Context Protocol (MCP) server for Pi-hole. This server exposes Pi-hole functionality as tools that can be used by AI assistants. ## Dependencies ### Docker - [Docker install guide](https://docs.docker.com/engine/install/) ### `uv` (Optional, for Development) If you want to run the application locally, use `uv`. Install it with your package manager of choice. ## Environment Create a `.env` file in the project root with your Pi-hole credentials: ``` # Primary Pi-hole (required) PIHOLE_URL=https://your-pihole.local/ PIHOLE_PASSWORD=your-admin-password #PIHOLE_NAME=Primary # optional, defaults to URL if unset # Secondary Pi-hole (optional) #PIHOLE2_URL=https://secondary-pihole.local/ #PIHOLE2_PASSWORD=password2 #PIHOLE2_NAME=Secondary # optional # Up to 4 Pi-holes: #PIHOLE3_URL=... #PIHOLE3_PASSWORD=... #PIHOLE3_NAME=... #PIHOLE4_URL=... #PIHOLE4_PASSWORD=... #PIHOLE4_NAME=... ``` ## Project Structure The project follows a modular organization for better maintainability: ``` / ├── main.py # Main application entry point ├── tools/ # Pi-hole tools organized by functionality │ ├── __init__.py │ ├── config.py # Configuration-related tools (DNS settings) │ └── metrics.py # Metrics and query-related tools ├── resources/ # MCP resources │ ├── __init__.py │ └── common.py # Common resources (piholes://, version://) ├── docker-compose.yml # Docker Compose configuration for production ├── docker-compose.dev.yml # Docker Compose for development with volume mounts └── Dockerfile # Docker build configuration ``` This structure separates the code into logical components while maintaining compatibility with all run modes. ## Running the Server There are several ways to run the Pi-hole MCP server: ### Using Docker (Recommended for Production) ```bash # Standard deployment docker-compose up -d ``` The server will be available at `ht…