Video Reader MCP

io.github.SylphxAI由 GitHub 帳號 SylphxAI 發布v0.1.0更新於 Oct 24, 2026

Evidence-first video MCP. Timeline document with ffprobe streams and subtitle cues.

已驗證STDIO僅桌面檔案與儲存媒體與設計

概覽

AI 產生的概覽

本機 MCP 伺服器,為助理提供可搜尋、帶時間戳的本機影片時間軸,並可依需求產生畫面證據。

可以做什麼
  • 讀取本機影片的容器中繼資料、串流、章節與內嵌字幕,quality 設定下可額外啟用 ffmpeg 場景偵測
  • 在內嵌字幕中搜尋引文並回傳帶時間戳的比對結果
  • 在已知時間戳處算圖、裁切或 OCR 單一影格作為後續證據
  • 將缺少 ffprobe 或字幕的情況明確回報為缺口,而不是自行猜測
適用情境
適合需要就本機影片檔案回答問題的情境,例如找出某句台詞、依章節摘要會議、定位示範中的某個時刻,並要求每個結論都能引用時間戳、串流索引或來源雜湊。不適合沒有內嵌字幕的影片,也不做語音轉寫。
執行需求
以本機 stdio 程序執行,通常透過 npm 套件以 npx 啟動;讀取中繼資料需要 ffprobe,引文搜尋需要影片自帶內嵌字幕。未宣告任何驗證、環境變數或標頭。儲存庫已封存,README 表示專案已合併到另一個套件。
安裝前請注意
README 說明儲存庫已封存並指向後繼套件,安裝前應確認維護狀態。它不做語音辨識、關鍵影格或轉寫:開啟 include_keyframes 或 include_transcript 只會回傳警告與空陣列。影格算圖與 OCR 在本機對你指定的檔案執行。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Video Reader MCP,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Merged into anymd (2026-09-25). anymd reads PDFs, Office files, EPUB, web pages, images and video into clean Markdown for AI agents: npx -y @sylphx/anymd. This repository is archived.

Cue

Video answers with timestamp-level proof

Cue gives agents a local video timeline they can search and cite. The default read returns container metadata, streams, chapters, and embedded subtitles. Scenes and frames are separate.

bash
npx -y @sylphx/cue

For Claude Code:

bash
claude mcp add cue -- npx -y @sylphx/cue

Read a local video

json
{  "sources": [{ "path": "/absolute/path/to/demo.mp4" }]}

That call uses the fast profile. It returns container metadata, streams, chapters, and embedded subtitles. It does not detect scenes, extract frames, or run speech recognition.

Then ask:

“Which chapter covers the pricing change?”

Cue returns chapter and subtitle locators with timestamp_ms and the source hash. It does not invent a transcript. A quote search matches embedded subtitles only. Render or crop a frame afterwards with video_evidence, once you have a timestamp.

Jobs Cue is built for

Ask your agentCue returns
“Find this quote.”a timestamped match in embedded subtitles, when those subtitles exist
“Summarize this meeting.”chapters and embedded subtitles
“Where is the code shown?”one frame from video_evidence at a known timestamp
“What changed in this demo?”scene boundaries when profile is quality or include_scenes is set
“Give me the useful moments.”chapters, embedded subtitles, warnings, and gaps

Tool surface

ToolPurpose
read_videoDefault fast profile: container metadata, streams, chapters, and embedded subtitles. Scenes are opt-in.
search_videoSearch embedded subtitle cues. It does not run speech recognition.
video_evidenceNamed follow-up: render, crop, or OCR one frame at a timestamp

Predictable defaults

  • Omitted profile is fast: container metadata, streams, chapters, and embedded subtitles. No scenes, frames, or speech recognition.
  • profile quality adds ffmpeg scene detection. It does not extract frames or run speech recognition.
  • include_keyframes and include_transcript stay off. Setting either one on the shipped server returns a warning and an empty array.
  • OCR stays on video_evidence.
  • No cloud video API or frame-by-frame vision model is required.
  • Missing ffprobe or embedded subtitles is reported as a gap, not guessed around.

Why agents trust it

Every claim can point back to timestamp_ms, a stream index, a subtitle range, or the source hash. A frame index is present only after video_evidence.

Companion MCP tools

ProductJob
CitraPDF answers with page-level proof
IrisImage facts and pixel evidence
SpineRepository architecture and impact
LocusExact code-chunk retrieval
LookoutWeb research with source excerpts

Each product is independent. Install only the tools your agent needs.

Development

bash
bun installbun run buildbun testcargo testbun run benchmark:public-proofbun run benchmark:release-gate

License

MIT

來源:README.md,提交 30773b7

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v0.1.0最新Sep 16, 2026

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