Skip to main content
Glama

export_photos

Export edited photos as JPEG files to a specified folder for sharing or backup. Creates the destination folder automatically and applies all development edits during export.

Instructions

Export photos as JPG to a destination folder.

Exports selected photos (or specific local_ids) with all develop edits applied as sRGB JPEG files to the given folder path. Creates the folder if it doesn't exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
destinationYes
local_idsNo
qualityNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The `export_photos` tool is defined as an async function decorated with `@mcp.tool()`. It handles input validation, constructs a payload, and calls the internal `_call` helper to execute the `catalog.export_photos` command.
    @mcp.tool()
    async def export_photos(
        destination: str,
        local_ids: list[int] | None = None,
        quality: int = 85,
    ) -> dict[str, Any]:
        """Export photos as JPG to a destination folder.
    
        Exports selected photos (or specific local_ids) with all develop
        edits applied as sRGB JPEG files to the given folder path.
        Creates the folder if it doesn't exist.
        """
        if not destination:
            raise ValueError("destination folder path is required")
        ids = validate_local_ids(local_ids)
        payload: dict[str, Any] = {
            "destination": destination,
            "quality": max(1, min(100, quality)),
        }
        if ids:
            payload["local_ids"] = ids
        return await _call("catalog.export_photos", payload, timeout_s=300.0)
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 of behavioral disclosure. It adds useful context: it applies edits, creates folders if needed, and specifies the output format. However, it lacks details on permissions, error handling, or side effects (e.g., file overwriting), leaving gaps for a mutation tool.

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 appropriately sized and front-loaded, with the first sentence stating the core purpose. Each subsequent sentence adds essential details (edits applied, folder creation) without redundancy, making it efficient and well-structured.

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?

Given the tool's complexity (mutation with 3 parameters) and no annotations, the description covers key aspects like purpose, behavior, and some parameters. With an output schema present, it does not need to explain return values, but could improve by addressing missing parameter details and behavioral risks.

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?

Schema description coverage is 0%, so the description must compensate. It explains 'destination' as a folder path and 'local_ids' for selecting photos, adding meaning beyond the schema. However, it does not cover the 'quality' parameter or provide details like format constraints, partially compensating for the low coverage.

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's purpose with a specific verb ('Export') and resource ('photos'), specifying the output format ('JPG') and destination ('to a destination folder'). It distinguishes itself from sibling tools by focusing on exporting with edits applied, unlike tools for editing, selecting, or managing photos.

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 for exporting photos with edits, but does not explicitly state when to use this tool versus alternatives (e.g., other export or file-handling tools). It mentions selecting photos or using local_ids, providing some context, but lacks clear exclusions or comparisons to sibling tools.

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/4xiomdev/lightroom-classic-mcp'

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