"Using YouTube to obtain and summarize video content" matching MCP servers:

A Model Context Protocol server that enables access to YouTube video content through transcripts, translations, summaries, and subtitle generation in various languages.

Combines Naver DataLab trends, blog/news search, translation, and Unsplash images into a single research pipeline for content creators. Generates comprehensive research reports from a single query.

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.

A Model-Context Protocol Server for YouTube in Jp

Enables AI agents to extract YouTube video metadata and generate high-quality multilingual transcriptions with voice activity detection, supporting 99 languages with translation capabilities and intelligent caching.

Translates Japanese text into English using the Textra API service, enabling LLMs with limited Japanese understanding to process Japanese instructions.

Enables fetching and analyzing YouTube video comments and replies through the YouTube Data API. Supports sorting by relevance or time and returns structured JSON data for comment analysis, summarization, and translation tasks.

MCP server for the Humanread novel publishing platform, enabling AI agents to upload, format, preview, review, translate, and publish novels in Markdown or safe HTML.

Enables bidirectional lookup of Mi'kmaq and English words with definitions and examples, and provides tools for learning and dictionary statistics, integrating seamlessly with AI-powered IDEs.

Enables LLMs to transcribe, analyze, and translate audio/video content through Gladia's API.

Enables AI-powered translation of YouTube videos into localized versions with synthesized voiceovers and avatar videos. Supports the full content pipeline from transcript extraction and translation to video generation and publishing across social platforms.

An all-in-one MCP server for transcription, supporting YouTube, audio, and video with translation, summarization, chapter generation, subtitle export, and batch processing via 19 tools.

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.

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.