Ardour Ultra MCP

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create_track

Create audio or MIDI tracks, or audio buses, in an Ardour session via Session APIs. Define name, kind, channels, and optionally preview with a dry run.

Instructions

Create an audio/MIDI track or audio bus using Session APIs.

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": {
      "request": "<request>"
    },
    "name": "create_track"
  }
}

Input Schema

Name	Required	Description	Default
`request`	Yes

Output Schema

Name	Required	Description	Default
`data`	No
`error`	No
`success`	No
`warnings`	No
`revision_after`	No
`changed_objects`	No
`revision_before`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 9, 2026

TDQS

C2.6/5.0

Behavior2/5

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

Annotations already declare this is a non-read-only, non-destructive, non-idempotent creation call, so the description needs to add operational detail — and it does not. It says nothing about the meaningfully unusual request fields (dry_run, confirm_delete, expected_revision) that imply preview and conflict/overwrite semantics for a create operation, nor about permission or session-connection requirements.

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

Conciseness4/5

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

One tight sentence with the verb and resource front-loaded and no filler. Its brevity is efficient but tips into under-specification given the complex request object.

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

Completeness2/5

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

An output schema exists, so return values need no coverage, and the annotations cover the safety profile. However, for a mutation tool with a nested request object containing dry_run, confirm_delete and expected_revision, the description leaves an agent unable to call it correctly without reverse-engineering the schema.

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

Parameters1/5

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

Schema description coverage is 0% and the description never mentions a single field. The only faint signal is the audio/MIDI/bus wording, which loosely maps to the 'kind' enum, but nothing explains name validation rules, channels, dry_run, confirm_delete, or expected_revision — parameters whose presence on a create call is non-obvious and needs explanation.

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

Purpose4/5

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

The description gives a specific verb and resource ('Create an audio/MIDI track or audio bus') and names the three target kinds, which separates it from siblings such as create_group and create_midi_region. It stops short of explicitly naming an alternative, but an agent can identify what the tool produces.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus ensure_bus for the 'bus' kind, or versus sibling creators like create_group or create_midi_region. No prerequisites, no caveats, no exclusions are stated, so the agent must infer the use case from the name alone.

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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