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rawtherapee-mcp-server

rawtherapee-mcp-server

by lucamarien
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

preview_raw

Generate a small JPEG preview of a RAW file to inspect composition, exposure, and color before full development. Optionally return the image inline for visual analysis.

Instructions

Generate a small preview JPEG for visual analysis.

Use this to create a quick preview of how a RAW file will look with specific processing settings. The preview is a small JPEG suitable for visual inspection of composition, exposure, and color. When return_image is True, the preview image is returned inline for the LLM to see. Params: file_path, profile_path, max_width, return_image

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": {
      "file_path": "<file_path>"
    },
    "name": "preview_raw"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_pathYes
profile_pathNo
max_widthNo
return_imageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.4

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, description carries full burden. It mentions JPEG generation and inline return but omits key behavioral details: file location, persistence, permissions, destructiveness. Creating a file implies mutating state, yet no clarification.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Relatively concise at four sentences. Front-loads purpose. Slight repetition of 'preview', but overall efficient. No wasted sentences.

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

Completeness2/5

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

For a 4-param tool with no output schema or annotations, the description is incomplete. It does not specify the return format (path vs. data URI) when return_image is False, nor does it clarify the behavior of optional parameters. Gaps leave an AI agent uncertain about expected output and parameter handling.

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 description must compensate. It lists four parameter names but provides no additional semantics: no types, ranges, formats, or examples. For instance, max_width lacks unit or bounds; file_path lacks path format.

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?

Clearly states it generates a small preview JPEG for visual analysis of RAW files with processing settings. Mentions composition, exposure, color. However, does not explicitly differentiate from other preview tools like preview_with_adjustments or preview_before_after, leaving some ambiguity.

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?

Describes the use case for quick previews and mentions inline return when return_image is True. But lacks when-not-to-use guidance or alternatives among sibling preview tools. Implicit usage but no exclusions.

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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