# autobrr-mcp

> autobrr-mcp — savagecore-autobrr-mcp. Use this tool when you need to manage and automate autobrr instances, solving problems such as complex filter configuration and release management. It provides a simplified interface to 104 API endpoints through 13 resource-scoped tools, accepting inputs like filter criteria and indexer settings, and outputting managed feeds, clients, and system configurations. This tool is ideal for use cases requiring automated autobrr instance management, such as integrating with large language models (LLMs) for streamlined workflow optimization.

Canonical page: https://skillsregistry.net/skills/savagecore-autobrr-mcp  
JSON: https://api.skillsregistry.net/v1/skills/savagecore-autobrr-mcp

## Description

MCP server exposing autobrr's full API as tools, enabling LLMs to read and manage filters, indexers, feeds, clients, actions, releases, and system config. It wraps approximately 104 endpoints into 13 resource-scoped tools for comprehensive autobrr instance management.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/qt6ng4bnag)
- **Repository:** <https://github.com/arr-mcps/autobrr-mcp>

## 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": "savagecore-autobrr-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/savagecore-autobrr-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/savagecore-autobrr-mcp/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