Skip to main content
Glama
4xiomdev

Lightroom Classic MCP

by 4xiomdev
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

list_local_params

Retrieve available local adjustment parameters for masks in Lightroom Classic to apply targeted edits to specific image areas.

Instructions

List available local_* adjustment parameters for masks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/lightroom_mcp_custom/server.py:708-711 (handler)
    The tool `list_local_params` is registered as an MCP tool and delegates the call to `_call("masks.list_local_params")`.
    @mcp.tool()
async def list_local_params() -> dict[str, Any]:
    """List available local_* adjustment parameters for masks."""
    return await _call("masks.list_local_params")

Tool Definition Quality

B3.2/5.0
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 states it's a list operation, implying read-only behavior, but doesn't cover aspects like rate limits, authentication needs, or what the output contains. This is a significant gap for a tool with zero annotation coverage.

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 directly states the tool's purpose without any unnecessary words. It's front-loaded and wastes no space, making it highly concise and well-structured.

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 has 0 parameters, 100% schema coverage, and an output schema exists, the description is adequate as a minimum viable explanation. However, it lacks details on behavioral traits and usage guidelines, which are important for a tool with no annotations, leaving some gaps in completeness.

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

Parameters4/5

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

The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description appropriately doesn't discuss parameters, aligning with the schema, which justifies a baseline score of 4 for this context.

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 verb ('List') and resource ('available local_* adjustment parameters for masks'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_develop_parameters' or 'get_local_adjustment_settings', which might be related, so it doesn't reach the highest score.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention any prerequisites, exclusions, or related tools, leaving the agent to infer usage from context alone.

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