# Radarr and Sonarr

> Use this tool when you need to manage and query movie and TV show collections with advanced filtering options. It solves problems of media library organization and discovery, providing access to detailed information on movies and TV series. The tool takes natural language inputs and outputs relevant media data, ideal for use in contexts where users interact with their media libraries using voice or text commands.

Canonical page: https://skillsregistry.net/skills/berrykuipers-radarr-sonarr  
JSON: https://api.skillsregistry.net/v1/skills/berrykuipers-radarr-sonarr

## Description

This MCP server provides AI assistants with access to Radarr (movies) and Sonarr (TV series) data. Built with FastMCP, it implements a standardized protocol for querying movie and TV show collections, offering rich filtering options by year, watched status, actors, and more. The server is designed for seamless integration with Claude Desktop and other MCP-compatible clients, enabling natural language interactions with media libraries.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-05-18

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/berrykuipers-radarr-sonarr)
- **Repository:** <https://github.com/berrykuipers/mcp_services_radarr_sonarr>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "berrykuipers-radarr-sonarr"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/berrykuipers-radarr-sonarr` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/berrykuipers-radarr-sonarr/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt
