PiHole MCP Server

Name: PiHole MCP Server
Author: NickJLange

@NickJLange

Repository

About PiHole MCP Server

No overview available yet

#pihole #mcp #server #fastapi #nlp

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "pihole_mcp_server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is PiHole MCP Server?

The PiHole MCP Server is a FastAPI-based RESTful service that enables natural-language query-based management and retrieval of statistics from Pi-hole devices using a Retrieval-Augmented Generation (RAG) system. It is designed for users who want to interact with their Pi-hole devices through natural language commands.

How to use PiHole MCP Server?

Clone the repository, set up a virtual environment, install dependencies from requirements.txt, and configure config.toml (with secrets in a .env file). Start the server with uvicorn main:app --host 0.0.0.0 --port 8000. Then send POST requests to the /query endpoint with an X-API-Key header and a JSON body containing the query.

Key features of PiHole MCP Server

RESTful API built with FastAPI for interacting with Pi-hole
Natural language query processing via a RAG system
Feature flags configurable in config.toml
API documentation available at /docs when running
Milvus database integration for retrieval-augmented generation

Use cases of PiHole MCP Server

Block internet access for a specified duration using natural language
Query Pi-hole statistics without manual API calls
Automate Pi-hole management tasks through a programmable interface

FAQ from PiHole MCP Server

What does the PiHole MCP Server do?

It provides a RESTful API that lets you manage and retrieve Pi-hole statistics using natural language queries, backed by a RAG system.

How do I install and run the server?

Clone the repo, create a Python virtual environment, run pip install -r requirements.txt, copy config.toml.example to config.toml and adjust settings, then execute uvicorn main:app --host 0.0.0.0 --port 8000.