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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM59351
Volume:
10 |
4 |
April 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The current research proposes a novel MCP-powered RAG over videos (video-RAG) model which facilitates interactive engagement with video content using natural language queries. The method ingests, analyzes, and indexes the video dataset so that it can perform semantic search and answer questions accurately through the use of MCP along with the Regie plugin for video retrieval and Cursor for acting as the MCP host in order to facilitate structured and intelligible answers. The retrieval process involves extracting contextually pertinent video clips with specific citations which include timestamp references that correspond to the requested information, thus reducing the need to manually navigate videos to extract information.
KEYWORDS
Publication Date
6/3/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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