"MiniMax MCP (Model Context Protocol) GitHub Repository" matching MCP servers:

A Model Context Protocol server that provides DeepL translation capabilities, allowing AI assistants to translate text between supported languages via the DeepL API.

Enables internationalization tasks such as language detection, hardcoded string extraction, translation JSON analysis, plural rule generation, and locale-aware formatting through the Model Context Protocol.

Natural voice conversations for AI assistants that brings human-like voice interactions to Claude, ChatGPT, and other LLMs through the Model Context Protocol (MCP).

Enables AI assistants to greet users in 7 different languages including English, Spanish, French, German, Japanese, Chinese, and Korean. A lightweight multilingual greeting tool for the Model Context Protocol.

Enables localization of React, Next.js, and Vue apps from an AI assistant by managing projects, languages, translations, glossaries, style guides, and GitHub repository integration.

This server implements the Model Context Protocol to provide sentiment analysis of text, returning polarity, subjectivity, and overall assessment (positive, negative, or neutral).

Model Context Protocol (MCP) server for the Royal Spanish Academy (RAE) API. It allows language models to interact with RAE's dictionary and linguistic resources.

MCP server for the HY-MT translation model, allowing AI assistants to perform high-quality translations across 38 languages via the Model Context Protocol.

Enables AI agents to read and write JSON translation files (i18n, i18next, react-i18next) via the Model Context Protocol.

A local-first multilingual dictionary, thesaurus, translation, lexical-relations, semantic-neighbour, and English wordplay server for the Model Context Protocol (MCP). It operates fully offline with read-only query access and no data mutation while running.

MCP server for translating PDFs using pdf2zh-next, preserving document context by extracting all text segments for LLM translation at once.

Official AllVoiceLab Model Context Protocol (MCP) server, supporting interaction with powerful text-to-speech and video translation APIs.

MCP server for managing i18n translation files — gives your AI agent full control over your app's translations without dumping entire locale files into context.

A language expression coach MCP server that provides native-sounding translations with cultural context, tone notes, and audio pronunciation for over 13 languages.

Provides translation tuning by adjusting model output for naturalness, tone, and script per language pair, supporting en-jp and en-es.

Enables law firms and legal professionals to turn Arabic and English contract files into structured, citable context, with clause segmentation, date conversion across Hijri and Gregorian calendars, party extraction, and anchor-based verification, all without API keys or network calls.

Provides AI models with tools to proofread and format Chinese text before delivery, covering typos, punctuation, casing, spacing, and platform-specific character limits. It runs as a zero-dependency MCP service so the model checks and fixes its own Chinese writing automatically.

Products, social posts, search results and AI answers from Amazon, TikTok, Google, ChatGPT and more, as MCP tools. Code mode: the model writes TypeScript against a typed client, run in a sandbox.

Translation QA for i18n locale files. Deterministic validators — missing keys, placeholder drift, collapsed plurals, glossary breaches — that need no API key, plus a review tool that hands translation pairs and judging criteria back to the calling agent, so meaning-level review runs on the model your client already has. Translation with your own LLM key is optional. JSON, Flutter .arb, Apple .

Delegates mechanical text-to-text tasks to a local LLM to save Claude subscription quota, reading files server-side so large content never enters Claude's context.

An intelligent PDF translation assistant specializing in academic papers with mathematical formulas, enabling context-aware translation with layout preservation.

Enables AI assistants and MCP clients to look up Gujarati words in real dictionary data for meanings, synonyms, idioms, and inflected forms, with source attribution and typo suggestions. It also tells the model when a word is not found so it avoids guessing.

A Model Context Protocol server that enables users to manage translations for their applications through SimpleLocalize's localization platform via natural language prompts in Cursor.

Translate Python between English and your language, with round-trip verification. Pack-based and reviewed, not model-guessed: translate files both ways, look up how terms render, check identifier names, and report how legible a codebase is in a language, all locally with uvx legesher-mcp.

A Model Context Protocol server that enables AI assistants to translate and rephrase text between numerous languages using the DeepL API.

Provides offline translation across 200+ languages using a local NLLB-200 model, with no data leaving your machine.

Gives AI assistants read-only access to a conference stream's live captions and translations, saved transcripts, glossary context, and audience questions, using a developer API key from the portal. It can also be used through a hosted HTTP endpoint at mcp.deafassistant.com, so clients can connect without installing anything.

Enables batch translation of arXiv, DOI, or paper-page LaTeX sources into Simplified Chinese and compilation of Chinese PDFs via XeLaTeX, using DeepSeek's deepseek-flash model with glossary, structure validation, resume, and QA.

Enables AI agents to inspect, audit and safely edit locale JSON files across flat, nested, and namespaced layouts without loading whole files into the model context, with compact token-efficient reads and write paths that cannot drop keys or overwrite silently. Ships ten tools plus slash-command prompts for project info, key search, reference lookup, translation upserts, and missing-translation audits.

Enables integration of DeepSeek's language models with MCP-compatible applications, offering features like chat completion, custom model selection, and parameter control for enhancing language-based interactions.