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TrackTag MCP Server

TrackTag MCP Server

by adigold
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

find_audio_files

Locate audio files on your computer by partial name across Downloads, Desktop, Music, and Documents. Resolve local file paths when you only have a track name.

Instructions

Find audio files on this machine by (partial) name — searches Downloads, Desktop, Music and Documents. Use this to resolve a file path when the user mentions a track by name (e.g. after dragging a file into chat, which does not reveal its local path). Free.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "find_audio_files"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesPart of the file name, case-insensitive (e.g. 'sunset drive')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the search directories and partial-name matching, but does not describe the return format (e.g., list of paths), behavior with zero results, or any potential side effects. The mention of 'Free' adds minimal value. Some behavioral context is present, but significant gaps remain.

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 description is two sentences, front-loaded with the core purpose, and contains no redundant information. Every sentence contributes to understanding the tool's function and use case.

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?

For a simple one-parameter tool, the description provides purpose, scope, search directories, and a concrete use case. It does not explicitly describe the return value, but the phrase 'resolve a file path' implies the output. Given the low complexity and no output schema, this is nearly complete, though a note about multiple matches or no results would elevate it.

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 fully describes the single parameter 'query' with a clear example. The description reinforces that it is a partial name but does not add additional semantic value beyond the schema. With 100% schema coverage, the baseline of 3 is appropriate.

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 clearly states the tool finds audio files on the machine by partial name, searches specific directories, and is distinct from sibling tools like analyze_track or list_recent_jobs. The verb 'Find' and resource 'audio files' make the purpose unambiguous.

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 a clear when-to-use scenario: resolving a file path when a user mentions a track by name, such as after dragging a file into chat. It lacks explicit exclusions or comparisons to alternatives, but the context is sufficient for basic selection.

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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