Skip to main content
Glama

get_selected_photos

Retrieve selected photos from Lightroom Classic with IDs and metadata for editing workflows. Use this tool to access photo details and manage catalog selections programmatically.

Instructions

List selected Lightroom photos with IDs and key metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The get_selected_photos tool handler implemented using the @mcp.tool decorator. It validates the limit and calls the underlying catalog command.
    @mcp.tool()
    async def get_selected_photos(limit: int = 200) -> dict[str, Any]:
        """List selected Lightroom photos with IDs and key metadata."""
        limit = max(1, min(int(limit), 1000))
        return await _call("catalog.get_selected_photos", {"limit": limit})
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists photos, implying a read-only operation, but does not specify whether it requires specific permissions, how it handles errors, or if it has rate limits. The description adds minimal behavioral context beyond the basic action, leaving gaps in understanding the tool's operational traits.

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, efficient sentence that front-loads the core purpose without unnecessary words. It directly states what the tool does, making it easy to parse and understand quickly. There is no wasted verbiage, and it effectively communicates the essential information in a compact form.

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 simplicity (one optional parameter, read-only operation implied), the description is reasonably complete. It specifies the resource and output format ('IDs and key metadata'), and with an output schema present, detailed return value explanations are not needed. However, it lacks context on usage scenarios and behavioral nuances, which slightly reduces completeness for an agent needing to invoke it correctly.

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 input schema has one parameter ('limit') with 0% description coverage, meaning the schema provides no semantic details. The description does not mention any parameters, so it adds no meaning beyond the schema. However, with only one parameter and an output schema present, the baseline is 3, as the schema structure alone offers some guidance, but the description fails to compensate for the lack of parameter documentation.

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 the tool's purpose: 'List selected Lightroom photos with IDs and key metadata.' It specifies the verb ('List'), resource ('selected Lightroom photos'), and scope ('with IDs and key metadata'). However, it does not explicitly differentiate from sibling tools like 'get_active_photo' or 'get_selected_photo_files', which reduces clarity in distinguishing usage contexts.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing photos to be selected in Lightroom, or compare it to siblings like 'get_selected_photo_files' (which might return files instead of metadata). Without such context, the agent may struggle to choose appropriately among similar 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