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OrellBuehler

Radarr MCP Server

by OrellBuehler

list_movies

List movies in the library with optional filters for search, tag, monitoring status, file presence, or quality profile. Returns a compact summary including id, title, year, and status to quickly assess your collection.

Instructions

List movies in the library as a compact summary (id, title, year, tmdbId, monitored, hasFile, status, quality, path, tags). Use get_movie for the full record. Filters are applied client-side because Radarr returns the whole library in one response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoReturn at most this many movies
searchNoCase-insensitive substring matched against title and original title
tag_idNoOnly movies carrying this tag id
has_fileNoOnly movies with a file on disk (true) or missing (false)
monitoredNoOnly monitored (true) or unmonitored (false)
quality_profile_idNoOnly movies on this quality profile

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It usefully discloses that Radarr returns the entire library in one response and that filtering happens client-side, which lets an agent anticipate performance and output size. It also lists the output fields. It could mention pagination or lack of server-side filtering more prominently, but the key behaviors are covered.

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?

Two sentences deliver the output shape, the alternative tool, and the crucial behavioral note about client-side filtering. Every clause earns its place, and the most important information is front-loaded.

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

Completeness5/5

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

For a read-only listing tool with fully documented parameters, the description plus schema is complete. It explains the return style, field set, filtering behavior, and the relationship to get_movie. No critical operational detail is missing.

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

Parameters3/5

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

The input schema already documents all six parameters with 100% coverage, so the baseline is 3. The description adds a general note about client-side filtering and the compact summary field list, but it does not add meaningfully to each parameter beyond what the schema states.

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 states a specific verb ('List'), a clear resource ('movies in the library'), and explicitly distinguishes this tool from get_movie by noting it returns a 'compact summary' with the exact fields included. This makes the tool's role unambiguous and easily separable from sibling tools.

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 gives clear context: use this for compact summaries and use get_movie for the full record. It also explains that filters are client-side because Radarr returns the whole library, which informs an agent about when this tool is appropriate. It doesn't enumerate exhaustive when-not scenarios, but the get_movie alternative is explicit.

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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