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Dorico MCP Server

Dorico MCP Server

by happycastle114
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

add_dynamics

Add dynamic markings such as pianissimo, forte, or sforzando to selected notes in Dorico scores. Choose from soft, medium, loud, or accented dynamics.

Instructions

Add a dynamic marking to the selection.

Args: dynamic: Dynamic marking. Options: - pppp, ppp, pp, p (soft) - mp, mf (medium) - f, ff, fff, ffff (loud) - fp, sf, sfz, fz, rf, rfz (accented)

Returns: Success status

Examples: - Piano: add_dynamics("p") - Forte: add_dynamics("f") - Sforzando: add_dynamics("sfz")

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": {
      "dynamic": "<dynamic>"
    },
    "name": "add_dynamics"
  }
}

Input Schema

NameRequiredDescriptionDefault
dynamicYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.2/5.0
Behavior4/5

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

Since no annotations are provided, the description carries full burden. It describes the action, lists all possible dynamic markings, and indicates the return value (success status). It does not cover prerequisites or error conditions, but it is sufficiently transparent for the tool's simplicity.

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 well-structured with sections for Args, Returns, and Examples. It is concise, with each sentence adding value, and no superfluous content.

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 tool is simple with a single parameter. The description fully explains the parameter, gives examples, and mentions the return value. It is complete for the tool's complexity and context.

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 has 0% description coverage, so the parameter 'dynamic' is fully undocumented in the schema. The description compensates completely by listing all allowed values with groupings and providing examples.

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 clearly states 'Add a dynamic marking to the selection', specifying verb and resource. It does not explicitly differentiate from sibling tools like 'balance_dynamics', but the purpose is unmistakable.

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

Usage Guidelines3/5

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

The description provides allowed values and examples, implying usage context. However, it does not mention when to use this tool versus alternatives, such as 'balance_dynamics' or other dynamic-related tools.

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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