Oraclarr MCP server

<!-- mcp-name: io.github.bdog720/oraclarr -->

Oraclarr

Ask your media stack what's going on, in plain language.

A locally-run, read-only MCP server that lets an LLM client (Claude Code, Claude Desktop) diagnose a self-hosted *arr media stack.

What it does

Oraclarr gives a language model one place to answer the operational "why" questions that normally mean tabbing through six web UIs. It aggregates across your services and returns a single, structured answer without changing anything (it is strictly read-only in this phase).

Covered now: Sonarr, Radarr, Prowlarr, qBittorrent, Tdarr, and Profilarr — including multiple instances of the same type (e.g. a separate anime or 4K Sonarr/Radarr). Every tool fans out across all the instances you define and reports each one separately.

In practice

Once registered, you just ask your MCP client. Oraclarr picks the right tool and answers:

Tools

All read-only and outcome-oriented (not one-per-endpoint, which keeps the model accurate):

Install

There are two ways to run Oraclarr — pick one, you don't need both:

arr stack. Best for homelabs; works great with Portainer, Dockge, Unraid, etc.

• 🐳 Docker (recommended) — a small always-on container that lives next to your

local development, or if you simply don't use Docker.

• 🐍 Python (uv) — run it directly on your machine with no container. Best for

Both options need the same two files. Make them from the templates in this repo — config.example.yaml (your service URLs) and .env.example (your API keys / passwords):

cp .env.example .env, then edit them.

• If you cloned the repo: cp config.example.yaml config.yaml and

copy their contents into a config.yaml and a .env in your stack folder, and fill in your details.

• If you're pasting into Dockge/Portainer: open those two example files above,

Shortened. The full README is on GitHub.