DaVinci Resolve MCP Server

resolve_generate_speech

Add spoken audio to the media pool without altering the timeline. Enter text up to 350 characters and choose a voice to generate a speech clip.

Instructions

Generate a speech clip into the media pool, leaving the timeline untouched. Requires AI Speech Generator Extras. Text is limited to 350 characters.

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": {
      "text": "<text>",
      "filename": "<filename>"
    },
    "name": "resolve_generate_speech"
  }
}

Input Schema

Name	Required	Default
`text`	Yes
`voice`	No	Female 1
`filename`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.2.0Sep 22, 2026

TDQS

A3.9/5.0

Behavior3/5

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

With no annotations, the description carries the behavioral burden. It usefully discloses the non-destructive nature and the prerequisite, but it does not describe output/return behavior, failure modes, or what happens when the 350-character limit is exceeded. This is adequate but not rich.

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 focused sentences with no filler. The primary action and the key constraint ('leaving the timeline untouched') are front-loaded, and the prerequisite and character limit follow efficiently.

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 relatively simple 3-parameter tool, the description covers purpose, output location, side-effect absence, prerequisite, and an input constraint. It lacks explicit return/result description and more parameter detail, but it is functionally complete enough for an agent to invoke the tool correctly.

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

Parameters2/5

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

Schema coverage is 0%, so the description must compensate for parameter meaning. It adds a character limit for 'text' but says nothing about 'voice' or 'filename' beyond their raw names. The schema only provides types and defaults, leaving the agent to guess filename expectations and voice value semantics.

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?

States a specific verb ('Generate'), a concrete resource ('a speech clip'), and the target location ('into the media pool'). Also distinguishes itself by explicitly saying 'leaving the timeline untouched,' which separates it from timeline-modifying siblings.

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?

Provides clear context: the tool is for speech generation into the media pool without touching the timeline, and it notes a prerequisite ('Requires AI Speech Generator Extras'). It does not explicitly name alternatives or exclusion cases, so it stops short of a full 5.

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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