Skip to main content
Glama
BaconDroid

libretranslate-mcp

by BaconDroid

Detect language

detect

Identify the language of text or up to 20 strings via a self-hosted LibreTranslate instance, returning confidence scores for each detection.

Instructions

Detect the language of one or more strings using a self-hosted LibreTranslate instance (POST /detect). Returns one detection per input string, in input order, with the confidence LibreTranslate reported when it provided one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesA single string, or an array of up to 20 strings, to detect.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the HTTP method (POST), the input shape (one or more strings), the output ordering (input order), and the confidence field (when provided). This is substantial behavioral context, though it omits error handling, authentication requirements, and rate limits.

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?

Two sentences, front-loaded with the core purpose, and each clause adds meaningful information (endpoint, input cardinality, output order, confidence). No redundancy or filler.

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?

For a single-parameter tool with no output schema, the description covers the essential return contract (per-input ordering, confidence). It doesn't discuss failure modes or edge cases (e.g., unsupported languages, empty array), but those are minor given the simplicity. Overall adequate for correct invocation.

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?

Schema coverage is 100%, so the parameter 'q' is fully documented with its type and constraints. The description reiterates 'one or more strings' but adds no new semantic detail (e.g., accepted language codes, format hints, or detection heuristics). It meets the baseline without extra value.

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 detects the language of one or more strings, names the specific endpoint (POST /detect), and describes the return behavior (one detection per input, in order, with confidence). This distinguishes it from siblings like 'translate' and 'languages' without needing to open their schemas.

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 purpose is clear but there is no explicit guidance on when to use this tool versus the siblings. It doesn't say 'use this to detect language before translating' or 'use languages to list supported codes.' The usage is implied by the verb and resource, but no alternatives or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools