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FreezeText MCP

FreezeText MCP

by juergenkoller-software
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get_ocr_languages

Retrieve the current OCR recognition languages to confirm which languages are configured for text extraction.

Instructions

Returns the currently configured OCR recognition languages.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_ocr_languages"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It only states that it returns configured languages, but does not confirm it is read-only, non-destructive, or clarify access requirements. The description fails to add transparency beyond the name and input schema.

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?

A single sentence that is clear and to the point. No extraneous words or filler. The description is optimally concise for the tool's simplicity.

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?

The description is complete enough for a minimal tool, but it lacks detail about the return format (e.g., list of language codes) and does not mention any side effects or state. Given no output schema, slightly more context would improve 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?

With zero parameters and 100% schema coverage, the description does not need to explain parameters. It adds no param info, but the baseline is 4 per the rubric since there are no parameters to describe. The description is adequate in this dimension.

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 returns currently configured OCR recognition languages. The verb 'returns' and the specific resource 'OCR recognition languages' make the purpose unambiguous. It is easily distinguished from sibling tools like set_ocr_languages (which sets) and ocr_image (which performs OCR).

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 explicit guidance on when to use this tool versus alternatives. While it is implied that it is for reading configurations, the description does not mention prerequisites or suggest pairing with other tools (e.g., check languages before OCR). A score of 2 reflects the lack of practical usage context.

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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