translate-text
Convert text into a target language using the DeepL API. Specify the language code and optionally adjust formality for translations. Designed for integration with AI assistants.
Instructions
Translate text to a target language using DeepL API
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| formality | No | Controls whether translations should lean toward informal or formal language | |
| targetLang | Yes | Target language code (e.g. 'en-US', 'de', 'fr') | |
| text | Yes | Text to translate |
Implementation Reference
- The handler function for the 'translate-text' tool. It translates the input text to the target language using the DeepL API client, returns the translated text and detected source language, or handles errors.
async function translateText({text, targetLang, formality}) { try { const result = await deeplClient.translateText( text, null, targetLang, { formality }); return mcpTextContentify([ result.text, 'Detected source language: ' + result.detectedSourceLang ]); } catch (error) { return handleError(error); } } - workshops/deepl-simple-js/deepl-simple.js:53-63 (registration)Registration of the 'translate-text' tool on the MCP server, including name, description, input schema, and handler reference.
server.tool( "translate-text", "Translate text to a target language using the DeepL API", { text: z.string().describe("Text to translate"), targetLang: z.string().describe("Target language ISO-639 code (e.g. 'en-US', 'de', 'fr')"), formality: z.enum(formalityTypes).optional() .describe("Controls whether translations should lean toward informal or formal language"), }, translateText ); - Input schema definition using Zod for validating tool parameters: text (string), targetLang (string), and optional formality (enum).
{ text: z.string().describe("Text to translate"), targetLang: z.string().describe("Target language ISO-639 code (e.g. 'en-US', 'de', 'fr')"), formality: z.enum(formalityTypes).optional() .describe("Controls whether translations should lean toward informal or formal language"), }, - Helper function to format strings into MCP-compatible text content objects, used in the handler to return results.
// Accept either a string or an array of strings, with partial error checking function mcpTextContentify(param) { if (typeof(param) != 'string' && !Array.isArray(param)) { throw new Error('mcpTextContentify() expects a string or an array of strings'); } const strings = typeof(param) == 'string' ? [param] : param; const contentObjects = strings.map( str => ({ type: "text", text: str }) ); return { content: contentObjects }; } - Helper function to handle and format errors for return in MCP format, called from the handler.
// Finally, a helper function to pass errors back to the AI surface function handleError(error) { console.error("Error in the DeepL MCP server: ", error); const errorContentObject = mcpTextContentify([error.message]); errorContentObject.isError = true; return errorContentObject; }