Skip to main content
Glama
luquimbo

DaVinci Resolve MCP Server

by luquimbo

timeline_export

Export the current DaVinci Resolve timeline to standard formats like AAF, EDL, FCPXML, and more, with optional sub-type selection for EDL exports.

Instructions

Export the current timeline to a file (AAF, EDL, FCPXML, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesAbsolute destination path for the exported file.
export_typeNoFormat to export. One of: "AAF", "DRT", "EDL", "FCPXML", "HDR10 Profile A", "HDR10 Profile B", "OTIO", "Text CSV", "Text Tab". Defaults to "AAF".AAF
export_subtypeNoSub-type for EDL exports. One of: "" (none), "SMPTE", "Avid", "CMX 3600". Defaults to "".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states that it exports the current timeline, but does not mention side effects like overwriting existing files, permission requirements, or prerequisite that a timeline must be loaded. This leaves significant behavioral ambiguity for an export operation.

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 a single, front-loaded sentence that directly states the tool's purpose. It contains no unnecessary words or repetition, making it appropriately concise and easy to parse.

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

Completeness3/5

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

Given the tool's moderate complexity (3 parameters), rich schema, and presence of an output schema, the description is adequate but not complete. It lacks context about prerequisites (e.g., active timeline), file overwrite behavior, and connection to related timeline tools, leaving gaps that the schema alone cannot fill.

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 schema already provides 100% coverage with descriptive text for all three parameters (file_path, export_type, export_subtype). The description adds no new parameter information beyond the schema's own definitions, so the baseline of 3 applies without compensation.

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 verb 'Export' and the resource 'current timeline' to a file, and lists common formats (AAF, EDL, FCPXML) which distinguishes it from sibling tools like render_* or project_export. It is specific and unambiguous.

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 implies usage when the current timeline needs to be exported to a file, but it does not explicitly state when to use it versus alternatives, nor provide any exclusions. There is no reference to sibling tools like timeline_render or project_export, leaving the 'when' largely implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/luquimbo/davinci-resolve-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server