Gemini MCP Server

by salviz

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JavaScript

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gemini_translate

Translate text into a target language using Gemini. Supports automatic source language detection.

Instructions

Translate text to a target language using Gemini

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": {
      "text": "<text>",
      "targetLanguage": "<targetLanguage>"
    },
    "name": "gemini_translate"
  }
}

Input Schema

Name	Required	Description
`text`	Yes	The text to translate
`model`	No	Model to use (default: gemini-3.1-pro-preview)
`sourceLanguage`	No	The source language (auto-detected if omitted)
`targetLanguage`	Yes	The language to translate into

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.0.0Jun 29, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations, the description must disclose behaviors like source auto-detection, model default, latency, or API requirements. It only repeats the basic purpose, leaving significant behavioral gaps for the agent.

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 one sentence, which is efficient. However, it could include a bit more detail without becoming verbose. The structure is front-loaded but too brief.

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?

The tool has 4 parameters, no output schema, and no annotations. The description fails to mention return value (text translation), error handling, or language format (code vs name). It is incomplete for the given complexity.

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 description coverage is 100%, so baseline is 3. The description adds no extra semantics beyond the schema's parameter descriptions, nor does it clarify format or usage for parameters like targetLanguage.

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 action (translate), the resource (text), and the goal (to a target language) using the Gemini model. It is distinct from sibling tools, which are primarily analytical or chat-based, so no confusion arises.

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 (e.g., gemini_chat for translation) or when not to use it. The description lacks context such as prerequisites or scenarios where auto-detection might fail.

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