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arr-mcps

autobrr-mcp

autobrr_filters

Create, delete, duplicate, list, fetch, and update autobrr filters, including toggling enabled state and managing notifications.

Instructions

autobrr filters operations on autobrr. Pass operation and an arguments dict matching that operation's parameters.

  • autobrr_create_filter(body={}) — Create a filter. WRITE: this modifies your autobrr instance.

  • autobrr_delete_filter(filter_id) — Delete a filter. DESTRUCTIVE: this deletes data.

  • autobrr_duplicate_filter(filter_id) — Duplicate a filter (creates a new filter and returns it). WRITE: this modifies your autobrr instance.

  • autobrr_get_filter(filter_id) — Fetch a single filter by id.

  • autobrr_get_filter_notifications(filter_id) — Fetch just the notifications array attached to a filter.

  • autobrr_list_filters(sort='', indexer=None) — List filters. Query params: sort (e.g. name-asc, priority-desc), indexer (repeatable).

  • autobrr_toggle_filter_enabled(filter_id, body={}) — Enable or disable a filter (body: {"enabled": bool}). WRITE: this modifies your autobrr instance.

  • autobrr_update_filter(filter_id, body={}) — Replace a filter. WRITE: this modifies your autobrr instance.

  • autobrr_update_filter_notifications(filter_id, body=[]) — Replace the notifications array on a filter (body is a list of filter notifications). WRITE: this modifies your autobrr instance.

  • autobrr_update_filter_partial(filter_id, body={}) — Partially update a filter (only supplied fields change). WRITE: this modifies your autobrr instance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNo
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It labels every mutating operation as WRITE, marks delete as DESTRUCTIVE, notes that duplicate creates and returns a new filter, and explains partial update semantics. It also includes the required body shape for toggle, which goes well beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening sentence states the invocation pattern, and each bullet is a tight, information-dense entry with operation name, arguments, and side-effect label. There is no fluff or redundancy despite the length required for 10 operations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all operations, mutation/destructive behavior, and list query parameters, and an output schema exists for return-value details. However, it does not document the available fields inside complex create/update bodies, which is a minor gap for a filter API.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema only exposes a generic `operation` and `arguments` object, but the description documents each operation's specific parameters, defaults, and query params (e.g., `filter_id`, `body={}`, `sort`, `indexer`). With 0% schema description coverage, this fully compensates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description immediately identifies this as the tool for autobrr filter operations and then enumerates 10 concrete operations with specific verbs (Create, Delete, Duplicate, Fetch, List, Update). This clearly differentiates it from sibling tools for other autobrr resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs the agent to pass an `operation` and an `arguments` dict matching the operation's parameters, and the bullet list gives each operation's signature. It does not explicitly state when not to use the tool or name sibling alternatives, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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