lidarr-mcp

lidarr-mcp

MCP server exposing Lidarr's full v1 REST API as tools for reading and managing artists, albums, tracks, queue, history, and more. It enables LLMs to interact with a Lidarr instance via natural language.

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README

lidarr-mcp

Part of the arr-mcps collection. MCP server exposing Lidarr's v1 REST API (OpenAPI 3.0.4) as tools, so an LLM can read and manage a Lidarr instance: artists, albums, tracks, track files, the download queue, wanted/missing, history, indexers, import lists, metadata profiles, custom formats, tags, commands, system status, and more. Full surface — reads and writes, with destructive tools flagged.

Built with FastMCP.

Getting an API key

Generate one in Lidarr Settings > General > Security. Auth is the X-Api-Key header.

Install

Download a wheel from the latest release and install it as a uv tool (no repo checkout needed):

uv tool install lidarr_mcp-*.whl

This puts a lidarr-mcp command on your PATH. Register it with Claude Code:

claude mcp add lidarr \
  --env LIDARR_URL=http://your-lidarr-host:8686 \
  --env LIDARR_API_KEY=<key> \
  -- lidarr-mcp

From source

uv sync
cp .env.example .env   # fill in LIDARR_URL and LIDARR_API_KEY
claude mcp add lidarr \
  --env LIDARR_URL=http://your-lidarr-host:8686 \
  --env LIDARR_API_KEY=<key> \
  -- uv run --directory /path/to/lidarr-mcp lidarr-mcp

Config

Env var Required Default
LIDARR_URL yes -
LIDARR_API_KEY yes* none (no X-Api-Key header sent if unset)

* Every API endpoint requires auth; practically you must set it, but the server still starts without one so errors surface from the API rather than at startup.

Tools

15 resource-scoped tools, each covering multiple Lidarr v1 endpoints (223 total) via an operation parameter. Call a tool with operation set to one of its listed operations and an arguments dict matching that operation's parameters — the tool's own description (visible to your MCP client) lists every operation, its signature, and a one-line doc. This keeps the full REST surface available while costing a fraction of the context budget of registering all 223 endpoints as separate tools.

Tool Operations Kind
lidarr_media_library 26 reads + writes
lidarr_profiles_formats 26 reads + writes
lidarr_config 25 reads + writes
lidarr_system_commands 23 reads + writes
lidarr_indexers 23 reads + writes
lidarr_notifications_metadata 18 reads + writes
lidarr_tags 18 reads + writes
lidarr_import_lists 16 reads + writes
lidarr_download_clients 11 reads + writes
lidarr_storage 10 reads + writes
lidarr_queue 9 reads + writes
lidarr_history_blocklist 7 reads + writes
lidarr_release_search 5 reads + writes
lidarr_wanted 4 read-only
lidarr_calendar 2 read-only

Example: lidarr_queue(operation="lidarr_delete_queue", arguments={"id": 42}). Endpoint-level naming (lidarr_<verb>_<resource>) is preserved as the operation value, so the full endpoint list is still discoverable from each group tool's description at runtime.

Development

make help  # list all commands
Command Does
make sync uv sync
make test Offline tests - one per endpoint, mocked HTTP
make test-integration Tests against the live instance (needs LIDARR_URL/LIDARR_API_KEY)
make build Build wheel + sdist into dist/
make bump-patch / bump-minor / bump-major Bump the version in pyproject.toml + uv.lock
make clean Remove build artifacts

The release workflow (.github/workflows/release.yml) builds and publishes to Releases whenever a v* tag is pushed - so the usual flow is make bump-patch, commit, then tag and push.

The integration suite is read-only by default (GET endpoints only). Set LIDARR_WRITE_TESTS=1 to also exercise POST/PUT/DELETE against a scratch tag (created, updated, then deleted). Never run write tests against a production library.

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