serato-dj-mcp

Audit the Serato library

audit_library

Read-onlyIdempotent

Diagnose your Serato DJ library with automated checks for missing BPM, unreadable keys, duplicates, broken paths, and more, returning counts and example track IDs.

Instructions

Diagnose the library. All checks run by default: missing_bpm, missing_key, key_unreadable_by_serato, stale, not_in_any_crate, streaming_only, duplicates, broken_paths. broken_paths reads Serato's own missing flag by default and ALSO walks the filesystem with check_filesystem: true -- opt-in because a stat against a disconnected drive blocks for seconds. Each check reports a count and up to 10 example track ids; duplicates reports groups instead, since which track duplicates which is the actionable part. missing_key counts tracks with no key at all, while key_unreadable_by_serato counts tracks whose key this server can read but Serato itself cannot display.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`checks`	No
`check_filesystem`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`checks`	Yes
`warnings`	No
`generation`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Sep 24, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses default behavior, per-check output shape, the special duplicates grouping, and the subtle distinction between missing_key and key_unreadable_by_serato. It also explains the filesystem-walk performance caveat.

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?

Every sentence earns its place: scope, defaults, the opt-in flag with rationale, output format, and an important distinction between two similar checks. It is dense but well-organized and 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?

The description covers what the tool does, what each check means, how the optional flag behaves, output structure, and safety profile via annotations. Even with an output schema present, this description leaves nothing material missing for correct invocation.

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?

With 0% schema description coverage, the description fully compensates by naming every valid check value, explaining that checks are optional via 'all checks run by default', and describing what check_filesystem: true actually does. This adds meaning the raw schema lacks.

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 opens with 'Diagnose the library' and then enumerates the eight concrete checks, giving a precise verb-resource-scope statement. This clearly differentiates it from sibling tools that list, search, or fetch tracks.

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?

It explains that all checks run by default and that the filesystem walk is opt-in due to a real blocking risk on disconnected drives. It does not explicitly name sibling alternatives, but the diagnostic-vs-access distinction is clear enough from context.

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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