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Lara Translate MCP Server

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translate

Read-only

Translate text between languages with automatic detection, context-aware adjustments, and optional glossaries. Supports multiple languages and style preferences.

Instructions

Translate text between languages using Lara Translate. Supports language detection, context-aware translations, translation memories, and glossaries. The optional 'instructions' parameter accepts short localization directives (e.g., 'Translate formally') — only provide them when the content specifically requires tone, formality, or terminology adjustments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesAn array of text blocks to translate. Each block contains a text string and a boolean indicating whether it should be translated. This allows for selective translation where some text blocks can be preserved in their original form while others are translated.
sourceNoThe source language code (e.g., 'en-EN' for English). If not specified, the system will attempt to detect it automatically. If you have a hint about the source language, you should specify it in the source_hint field.
targetYesThe target language code (e.g., 'it-IT' for Italian). This specifies the language you want the text translated into.
contextNoAdditional context string to improve translation quality (e.g., 'This is a legal document' or 'Im talking with a doctor'). This helps the translation system better understand the domain.
instructionsNoOptional list of short localization directives to adjust translation output. Each instruction MUST be no more than 20 words. These are NOT free-form LLM prompts — they are expert localization directives about formality, tone, or domain-specific terminology. Only provide instructions when the content specifically requires them; omitting instructions for general content preserves higher translation quality. Do NOT combine contradictory instructions (e.g., formal and informal tone together). Examples: 'Translate formally', 'Use a creative and concise tone', 'Make translation gender-neutral', 'Mask any price with the [price] placeholder', 'Use quotation marks (« ») for quotations'.
source_hintNoUsed to guide language detection. Specify this when the source language is uncertain to improve detection accuracy.
adapt_toNoA list of translation memory IDs for adapting the translation.
glossariesNoArray of glossary IDs to apply during translation (max 10). IDs must match format: gls_* (e.g., ['gls_xyz123', 'gls_abc456']). Glossaries enforce specific terminology and terms.
no_traceNoPrivacy flag. If set to true, the request content will not be stored or traced by Lara. Use for sensitive content.
priorityNoTranslation priority. 'normal' for real-time translations, 'background' for batch processing with lower priority.
timeout_in_millisNoCustom timeout for the translation request in milliseconds. Max: 300000ms (5 minutes). Useful for very long texts.
styleNoControls how the translation balances accuracy against natural readability. 'faithful' stays close to the source, 'fluid' prioritizes natural readability, 'creative' allows more freedom in the translation.
reasoningNoEnables Lara Think multi-step linguistic analysis. Can increase processing time up to 10x but may improve translation quality for complex texts.
content_typeNoSpecifies the content type of the text. Autodetected if omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesTranslated text blocks, in the same order and structure as the input. Blocks marked translatable: false are preserved verbatim.
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the tool is understood as non-modifying. The description adds valuable behavioral context by listing supported features (language detection, context-aware, memories, glossaries), which goes beyond the bare annotations. It does not contradict annotations.

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?

The description is concise at two sentences. The first sentence front-loads the main purpose. The second sentence provides focused guidance on a key parameter. It is efficient but could potentially be more structured to differentiate from siblings.

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 complexity (14 parameters, output schema exists), the description covers core functionality but lacks guidance on when to use this tool versus highly related siblings like detect_language or add_translation. The output schema is not explained, but that is acceptable since it exists separately.

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 provides detailed descriptions for all 14 parameters (100% coverage). The description adds minimal new semantic value beyond highlighting the 'instructions' parameter behavior. The baseline of 3 is appropriate as the schema already carries the burden.

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 primary function: 'Translate text between languages using Lara Translate.' It enumerates specific capabilities (language detection, context-aware translations, memories, glossaries) and implicitly distinguishes it from sibling tools like detect_language, add_translation, and glossary management tools.

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 provides guidance on when to use the 'instructions' parameter ('only provide them when the content specifically requires tone, formality, or terminology adjustments') and advises omitting it for general content. However, it lacks explicit guidance on when to choose this tool over alternatives like detect_language or add_translation for different translation scenarios.

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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