🍓 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

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)

# Standard deployment
docker-compose up -d

The server will be available at http://localhost:8383

Development Mode with Docker

For development, use the dev compose file which builds locally:

docker-compose -f docker-compose.dev.yml up

MCP Inspector

You can run the MCP inspector using uv and the mcp CLI:

uv run mcp dev main.py

This will start an interactive interface at http://localhost:6274 where you can test tools and resources.

API

This MCP server exposes the following resources and tools:

Resources

• piholes://: Returns information about all configured Pi-holes
• version://: Returns the MCP server version
• list-tools://: Returns a list of tool categories
  • list-tools://{category}: Returns a list of tools within a specific category

Tools

Each tool call returns results as a list of dictionaries with the following structure:

[
  {
    "pihole": "Pi-hole Name",
    "data": [...]  # Result data from this Pi-hole
  },
  ...
]

Configuration

• list_local_dns: Lists all local DNS settings from Pi-hole(s)
• add_local_a_record: Adds a local A record to Pi-hole(s).
• add_local_cname_record: Adds a local CNAME record to Pi-hole(s).
• remove_local_a_record: Removes all A records for a hostname.
• remove_local_cname_record: Removes all CNAME records for a hostname.

Metrics

• list_queries: Fetches the recent DNS query history from Pi-hole(s)
• list_query_suggestions: Get query filter suggestions
• list_query_history: Get activity graph data for queries over time

Testing in goose

Goose is a CLI LLM client that's useful for testing and development. Follow their install instructions here.

The following assumes you've completed the initial setup with goose configure.

Configure Extension

1. Type goose configure to open the configuration menu.
2. Select Add Extension
3. Select Remote Extension
4. It will ask for a name. It doesn't matter what you name it. I called mine `pihole-

... View full README on GitHub