Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Lidarr MCP Servershow me my recently added artists"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
lidarr-mcp
Python MCP (toolkit) to interact with a Lidarr instance. Designed to be used as a local "toolkit" for LLM integrations (e.g. Claude) or as a CLI. An optional FastAPI server is provided if you prefer HTTP tooling.
Goals
Provide Python functions (tools) to list / get / create / update / delete artists, albums (releases) and tracks via Lidarr's API.
Provide a CLI (Typer) to call these tools from the shell.
Provide an optional FastAPI server to expose these tools over HTTP if needed.
Quick start
Clone the repo and create a virtualenv python -m venv .venv ..venv\Scripts\Activate.ps1 # or ..venv\Scripts\activate.bat
Install dependencies pip install -r requirements.txt
Copy .env.example to .env and set LIDARR_URL and LIDARR_API_KEY
Use the CLI python -m lidarr_mcp.cli artists list
How to plug this repo to Claude
Option A (recommended local tooling): Run the CLI locally and configure Claude (or your LLM environment) so it can execute shell commands that call this CLI. For example, run the CLI via a controlled shell tool that your Claude instance can call.
Option B (HTTP tool): Run the optional FastAPI server (python -m lidarr_mcp.server) and configure Claude to call the endpoints. This is provided for convenience but is not required.
Files created in this initial commit: CLI (Typer), lidarr client wrapper, tools module, optional FastAPI server, Dockerfile and docker-compose, .env.example.
This server cannot be installed
Resources
Looking for Admin?
Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.