Vindex MCP Server
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- AlicenseNot gradedqualityBmaintenanceEnables LLM agents to process local videos into timestamped, citable text documents and then query them through tools for listing videos, retrieving transcripts, and fetching specific segments, all fully offline.MIT
- AlicenseNot gradedqualityBmaintenanceEnables an agent to process local video files and then read, search and inspect the results: timestamped transcripts, on-screen text and key frames as images. Everything runs locally, so an agent can answer questions like how to perform a task shown in a screencast or meeting recording.448 npm1MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query local video timelines by extracting speech, frame captions, and on-screen text into a SQLite store, exposing search and retrieval tools via MCP.PolyForm Noncommercial 1.0.0
- AlicenseAqualityDmaintenanceLet AI agents watch videos: local transcripts, speaker labels, scenes, chapters and exact-moment search from any video URL or file. Fully local, no API keys.43AGPL 3.0
- AlicenseNot gradedqualityBmaintenanceEnables any agent or LLM to read and query a video cheaply from a locally built context index, exposing text-layer overviews, per-shot thumbnails, on-demand frame retrieval, transcript search, and indexing tools. The server makes no model calls and needs no API key, letting the calling agent's own model reason over the text layer and fetched frames.1Apache 2.0
- AlicenseAqualityCmaintenanceEnables AI agents to index videos locally once and then browse a compact text map of shots, transcript, silences and visual embeddings, so they can query moments, cut dead air, apply edit scripts, render with ffmpeg and run QA checks without spending tokens on frames. Pixels are only fetched when the agent explicitly peeks at labeled contact sheets.9MIT
TDQS
Scored across 5 tools
The tools generally have distinct roles across ingest, status, search, shot inspection, and transcript retrieval. There is some overlap because search_corpus and get_shot_context both return transcript/filmstrip context, and get_transcript can be confused with transcript fields returned by other tools, but the descriptions make the intended boundaries reasonably clear.
All tool names use consistent snake_case with a clear verb_noun or verb_noun_object pattern: ingest_video, get_ingest_status, search_corpus, get_shot_context, get_transcript. The naming is predictable and easy to infer.
Five tools is well scoped for a video ingestion and retrieval server. Each tool covers a distinct stage of the workflow from ingestion through search and contextual inspection, with no obviously redundant tools.
The core lifecycle is covered: ingest, check status, search, inspect shot context, and retrieve transcripts. Minor gaps remain around corpus/video management, such as listing ingested videos or deleting/removing bundles, which agents may need for cleanup or discovery.