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⇱ Video content analysis and understanding for large language models | Glama

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Video content analysis and understanding for large language models

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  • Why this server?

    This server is an excellent fit because it explicitly extracts and transcribes audio content from videos across multiple streaming platforms (YouTube, Bilibili, TikTok, Twitter), which directly enables an LLM to 'know video content'.

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    A service that extracts and transcribes audio content from videos across 1000+ streaming websites including YouTube, Bilibili, TikTok, and Twitter, supporting multiple transcription providers like Deepgram, Gladia, Speechmatics, and AssemblyAI.
    Last updated
    28
    MIT

  • Why this server?

    This server is a strong match as it directly provides tools for 'video recognition' using Google's Gemini AI, allowing an LLM to 'watch videos' and understand their content.

  • Why this server?

    This server is a perfect fit, described as a 'video analysis system that uses AI vision models to process, analyze, and query video content through natural language', directly addressing the user's need to 'watch videos' and 'know video content'.

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    A video analysis system that uses AI vision models to process, analyze, and query video content through natural language, enabling users to search videos by time, location, and content.
    Last updated
    5
    MIT

  • Why this server?

    This server specifically utilizes Google Gemini Vision API to 'interact with YouTube videos', enabling an LLM to 'get descriptions, summaries, answers to questions, and extract key moments', which directly fulfills the user's request.

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    MCP (Model Context Protocol) server that utilizes the Google Gemini Vision API to interact with YouTube videos. It allows users to get descriptions, summaries, answers to questions, and extract key moments from YouTube videos.
    Last updated
    4
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    MIT

  • Why this server?

    This server directly enables 'video analysis by downloading and processing closed captions to create summaries of YouTube videos', making it highly relevant for an LLM to 'know video content'.

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    Bridges YouTube API and AI assistants, enabling video analysis by downloading and processing closed captions to create summaries of YouTube videos.
    Last updated
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    19
    MIT

  • Why this server?

    This server allows Claude AI to 'extract transcripts from YouTube videos', providing the text content necessary for an LLM to 'know video content'.

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    Enables Claude AI to extract transcripts from YouTube videos with zero setup required. Works on all platforms including mobile, supports multiple languages, and handles all YouTube URL formats through a cloud-hosted service.
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    90
    MIT

  • Why this server?

    This server is designed to 'analyze YouTube videos, enabling users to extract transcripts, generate summaries, and query video content using Gemini AI', directly meeting the requirements for an LLM to understand video content.

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    A Model Context Protocol server that analyzes YouTube videos, enabling users to extract transcripts, generate summaries, and query video content using Gemini AI.
    Last updated
    13
    MIT

  • Why this server?

    This server enables interaction with 'Google's Video Intelligence API for advanced video analysis', making it a strong candidate for an LLM to 'watch videos' and 'know video content' through sophisticated AI processing.

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    This server enables interaction with Google's Video Intelligence API for advanced video analysis, auto-generated using AG2's MCP builder to provide a standardized multi-agent interface.
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  • Why this server?

    This server explicitly 'enables asking questions about image, audio, or video files using state-of-the-art multimodal models', which is directly aligned with the user's goal of an LLM knowing video content through interaction.

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    Enables asking questions about image, audio, or video files using state-of-the-art multimodal models. Powered by fal.ai for advanced media analysis and understanding capabilities.
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