The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.

A Bilibili video search server based on the Model Context Protocol (MCP), providing API interfaces to support video content search, paginated queries, and video information return, including LangChain call examples and test scripts.

MiniMax's official Model Context Protocol (MCP) server supports interactions with APIs such as text-to-speech, video/image generation.

The YouTube MCP Server is a standardized interface implementation that allows AI language models to interact with YouTube content through protocols, providing functions such as video information retrieval, subtitle management, channel and playlist management.

Awesome MCP Security is a collection of resources related to the security of the Model Context Protocol (MCP), including security considerations, papers, videos, articles, tools, and servers, aiming to help users understand and address MCP - related security challenges.

The YouTube MCP Server is a service that implements the Model Context Protocol (MCP). It provides a standardized interface for AI language models to interact with YouTube content, supporting functions such as video information retrieval, subtitle management, channel and playlist operations, etc.

Luma API MCP is a project that provides image and video generation services. Users can access it through an API key, supporting multiple aspect ratios, models, and resolution options, and can control the generation effect through reference images or video keyframes.

MiniMax MCP JS is a MiniMax Model Context Protocol toolkit implemented in JavaScript/TypeScript, providing functions such as text-to-speech, image generation, video generation, and voice cloning, and supporting multiple configuration methods and transmission modes.

The Unsloth MCP Server is a server for efficiently fine-tuning large language models. Through optimized algorithms and 4-bit quantization technology, it achieves a 2-fold increase in training speed and an 80% reduction in video memory usage, supporting multiple mainstream models.

The YouTube MCP Server is a tool for obtaining and extracting subtitles from YouTube videos, enabling AI language models to access and process video content.

A video, audio, and text extraction server based on the MCP protocol, supporting video downloads from multiple platforms and using the Whisper model for speech-to-text processing

The implementation of the 360 AI Cloud Disk MCP Service allows AI models to interact with the cloud disk through a standard protocol, providing intelligent operation capabilities such as file management, upload and download, and video processing.

Pixeltable's multi-modal model context protocol server set provides indexing and querying functions for audio, video, images, and documents

The AI Video Generation MCP Server supports text and image input to generate dynamic videos, providing multiple parameter controls and model selections.

The Jianying video production MCP server is an automated tool based on the Model Context Protocol, enabling AI assistants to create professional video content through natural language, supporting automatic creation of Jianying drafts, adding materials, applying special effects, and exporting project files.

A server tool based on the Model Context Protocol, used to extract subtitle text from YouTube videos. It supports integration with Cursor and Claude Desktop, facilitating AI to directly analyze video content.

Tencent Cloud COS MCP Server is a service that allows large models to quickly access Tencent Cloud Storage (COS) and CI capabilities without coding, providing cloud storage and processing functions such as file upload and download, image processing, and video processing.

The YouTube MCP server is a comprehensive model context protocol server that provides real-time YouTube data access through the YouTube Data API v3. It supports 14 functions, including video detail retrieval, channel analysis, content evaluation, and caption extraction, and is suitable for AI assistant integration.

This project is a video generation MCP server based on the Google Veo2 model. It supports video generation through text prompts or images and provides MCP resource access functions.

Tencent Cloud COS MCP Server is a service based on the MCP protocol that allows large models to quickly access Tencent Cloud Storage (COS) and Cloud Infinite (CI) capabilities without coding, providing cloud storage and processing functions such as file upload and download, image processing, and video frame extraction.

A service based on the Model Context Protocol (MCP) that can automatically extract subtitles from YouTube videos and generate professional LinkedIn post drafts.

A Pixabay API service based on the MCP protocol, providing image and video search functions for AI models.

The OpenCV MCP Server is a Python - based computer vision service that provides OpenCV's image and video processing capabilities through the Model Context Protocol (MCP). It offers a full set of computer vision tools from basic image processing to advanced object detection for AI assistants and language models, including image processing, edge detection, face recognition, video analysis, and real - time object tracking.

The Vidu MCP Server is a server based on the Model Context Protocol, used to interact with the Vidu video generation API, providing functions such as image - to - video conversion, generation status check, and image upload.

The MCP API is a watermark removal service for Sora2 videos based on the model context protocol. It can be quickly integrated into mainstream MCP-compatible tools such as Claude Desktop and OpenAI, and can intelligently remove video watermarks through simple API key authentication.

The Luma AI MCP Server is a service based on the Model Context Protocol, integrating the Luma AI Dream Machine API (v1), providing a toolset for AI-generated videos/images, including text/image-to-video, video extension, audio addition, image quality improvement, etc., and supports direct calls through Claude Desktop.

The MCP server for YouTube video transcript extraction supports multi - language transcript acquisition, making it convenient for AI models like Claude to directly use video transcript content.

An MCP server based on the fal.ai API for generating images and videos, supporting the extension of different models and API endpoints.

An MCP server implementation based on the YouTube Data API, providing a standardized interface for AI language models to access YouTube content, including functions such as video information, subtitle management, channel analysis, and trend analysis.

The Vidu MCP Server is an interface service based on the Model Context Protocol for interacting with the Vidu video generation API, providing functions such as image - to - video conversion, task status query, and image upload.

The Supadata MCP server is an implementation of the model context protocol server that integrates Supadata's video and web page crawling capabilities. It provides functions such as video transcription extraction, web page crawling, scraping, and discovery, and supports automatic retry and rate limiting.

ComfyUI_StoryDiffusion is a plugin based on ComfyUI that supports the StoryDiffusion and MS - Diffusion models for generating coherent long - sequence images and videos. The project supports multiple functions, including dual - character co - appearance, ControlNet control, Lora acceleration, text - to - image and image - to - image conversion, etc.

The CloudGlue MCP service is a bridge connecting AI assistants and video data. It processes video content in a structured way so that it can be understood and used by large language models.

A YouTube data interaction server based on the Model Context Protocol, providing query and analysis functions for resources such as videos, channels, comments, and subtitles.

This project is a collection of multimodal model context protocol servers by Pixeltable, providing indexing and querying services for audio, video, images, and documents, and supporting local Docker deployment.