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Builds a searchable knowledge base from YouTube video transcripts with hybrid semantic and keyword search. Allows LLM assistants to search, organize, and retrieve timestamped information from videos you've watched.

A local MCP server for extracting YouTube video transcripts, metadata, and performing visual analysis using Gemini Vision or local Whisper models. It enables users to process video content through various tools for subtitle retrieval and frame analysis.

An MCP server agent that enables analysis of YouTube videos by extracting transcripts, generating summaries, and creating chapter timestamps. It allows users to interact with video content through natural language to perform tasks such as writing social media posts.

Enables interaction with YouTube through search and transcript extraction functionality. Allows searching for videos and retrieving full transcripts with timestamps for content analysis.

Enables AI models to interact with YouTube content including video details, transcripts, channel information, playlists, and search functionality through the YouTube Data API.

Enables interaction with YouTube through the YouTube Data API, allowing users to search for videos, playlists, and channels, generate video titles using AI, and manage YouTube content through natural language commands.

A Model Context Protocol server that provides comprehensive YouTube search functionality, enabling users to search for videos, channels, and playlists with advanced filtering options using the YouTube Data API.

YouTube Skills (TranscriptAPI) is the production API for extracting, searching, and analyzing YouTube content at scale. While other tools break when YouTube changes or cap you at 100 requests/day, TranscriptAPI serves 15 million transcripts monthly at 49ms median response time.

Enables AI assistants to search YouTube videos using the official YouTube Data API v3, extract full video transcripts in multiple languages, and store/retrieve video summaries using a local database.

An MCP server that provides YouTube data access without API keys or quotas. It enables agents to search videos, retrieve transcripts and metadata, and perform full-text search across cached content for AI context retrieval.

An MCP server that enables interaction with the YouTube Data API, allowing users to search videos, get video and channel details, analyze trends, and fetch video transcripts.

Analyzes YouTube videos using Google's Gemini API, allowing users to get summaries or ask questions about video content via direct URL input.

Yuyuanweb MCP

全面解析MCP Mianshiya ServerMCP Server的核心功能、安装配置和实用案例。作为顶级Model Context Protocol服务器，MCP Mianshiya Server能让AI助手访问实时数据、执行操作，为您提供更智能的工作体验和自动化解决方案。

Provides filesystem access and integration with Z.ai's GLM-4 models for code generation and reasoning tasks. Designed to work as a git submodule with automatic parent repository detection.

An MCP (Model Context Protocol) server that provides tools for uploading videos, creating processing tasks, and monitoring their progress through the ZapCap API.

An APAC-native web scraping API for AI agents that provides tools for scraping, crawling, searching, and extracting structured data from websites, directly usable from MCP-compatible clients like Claude Desktop, Cursor, and Windsurf.

Orchestrates multiple AI models (Gemini, OpenAI, Claude, local models) within a single conversation context, enabling collaborative workflows like multi-model code reviews, consensus building, and CLI-to-CLI bridging for specialized tasks.

Gives Claude Desktop access to multiple AI models (Gemini, OpenAI, OpenRouter, Ollama) for enhanced development capabilities including extended reasoning, collaborative development, code review, debugging, and large context analysis with conversation threading.

Gives Claude access to multiple AI models (Gemini, OpenAI, OpenRouter, Ollama) for enhanced development capabilities including extended reasoning, collaborative development, code review, and advanced debugging.

A Model Context Protocol server that gives Claude access to multiple AI models (Gemini, OpenAI, OpenRouter) for enhanced code analysis, problem-solving, and collaborative development through AI orchestration with conversations that continue across tasks.