"Repository information for My-FastMCP-Development-Assistant-MCP on GitHub" matching MCP servers:

MCP server that automates WebGAL game development tasks such as resource management, script editing, documentation lookup, and AI-powered voice generation using LLMs.

Provides translation capabilities using the DeepL API, supporting text translation between numerous languages, rephrasing, batch translation, document translation, and language detection with formality control.

Lets AI agents read and write the Calibre Ebook Translator plugin's translation cache chunk by chunk, enabling direct book translation workflows without manual copy-paste.

Provides access to Whissle AI services for speech-to-text, speaker diarization, translation, and text summarization. It enables users to process various audio formats and manage text content through natural language tools.

A simple MCP server that generates multi-language greetings and provides server information using the FastMCP framework.

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.

An MCP (Multi-Agent Conversation Protocol) Server that enables AI agents to interact with Google's Cloud Translation API for translating text between languages.

Votars is the world's smartest multilingual meeting assistant, designed for voice recording, transcription, and advanced AI processing. It features real-time translation, intelligent error correction, AI summarization, smart content generation, and AI discussions. The Votars app is available on Web,

MCP server that provides grounded Arabic dictionary lookup, enabling AI agents to search word roots, inflections, and meanings from real dictionary data.

Search Japanese onomatopoeia by scene, not by spelling. 161 entries with nuance explained in Japanese and English. Fully offline MCP server, no API key required.

AI localization from your editor — translate an app's string files into 46 languages with placeholder-safe, reproducible output. Eleven formats (JSON, .arb, .po, .strings, Android XML and more), and every translation is read back and checked before it lands.

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.

Translation quality evaluation MCP Server powered by xCOMET. Provides quality scoring (0-1), error detection with severity levels, and optimized batch processing for AI-assisted translation workflows.

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

English-first Korean equity intelligence MCP — translates Korean DART filings, foreign-holder 5%-rule flows (BlackRock / Vanguard / Norges / GIC plus 16 more), activist filings (KCGI / Align / ValueAct / Elliott), and KRX industry news to English on demand. 7 MCP tools, OSS self-host under AGPL-3.0.

Integrates the levelang.app translation API with AI assistants to provide translations constrained to specific learner proficiency levels. It supports multiple languages and allows users to control translation styles and moods while dynamically discovering available language configurations.

Enables fetching YouTube video transcripts from any URL without API keys, browser, or OAuth, with honest error reporting for missing transcripts and support for multiple languages, formats, and resilient provider fallbacks.

Enables AI agents to transliterate between Latin-script Javanese and Aksara Jawa (Hanacaraka) bidirectionally.

Provides access to the Database of Icelandic Morphology (BÍN) to look up word inflections, variants, and lemmas. It enables LLMs to answer grammatical questions and retrieve specific Icelandic word forms using standard grammatical tags.