video-search-and-summarization

NVIDIA Video Search and Summarization Blueprint enables real-time video analytics, visual question answering, and automated reporting.

MCPResearchOpen sourceNVIDIAGPU加速视频分析

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Type: MCP
Transport: http
Open source: Yes
GitHub Stars: ★ 1.8k
Source: mcp-github
Repository: github.com/NVIDIA-AI-Blueprints/video-search-and-summarization

Overview

The NVIDIA AI Blueprint for Video Search and Summarization (VSS) is a GPU-accelerated reference architecture for building video analysis agents with real-time alerting, visual question answering, and automated reporting. This blueprint leverages visual language models (VLMs) and large language models (LLMs) such as NVIDIA Cosmos and NVIDIA Nemotron. Accessible via the MCP protocol, it is suitable for scenarios requiring efficient video processing and analysis. Ideal for video analysts, IT engineers, and machine learning engineers.

Capabilities

▪Real-time video feature extraction
▪Visual question answering
▪Automated report generation
▪Video embedding search
▪Long-form video summarization

Use cases

Smart space monitoringWarehouse automationStandard operating procedure validationAnomaly detection

Setup

Requires: API KeyNode环境GPU支持

Refer to the quick start guide in the official documentation for installation and configuration.

This information was compiled by AI from public sources and may contain inaccuracies — please refer to the source.

FAQ

Who is this blueprint for?

It is suitable for video analysts, IT engineers, and machine learning engineers.

Does it require GPU support?

Yes, GPU support is required for acceleration.

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