Cue

io.github.SylphxAIPublished by GitHub account SylphxAIv0.3.5Updated Oct 24, 2026

Cue — video answers with timestamp-level proof. Scenes and frames stay off until asked.

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Overview

AI-generated overview

Cue is a local MCP server that gives an assistant a searchable video timeline for local video files, returning chapters, embedded subtitles and timestamped loc.

What you can do
Read local video files for container metadata, streams, chapters and embedded subtitles, with scene detection opt-in via a quality profile or scene flag. Search embedded subtitle cues for a quote and get timestamped matches. Render, crop or OCR a single frame at a known timestamp as follow-up evidence. Report gaps such as missing ffprobe or absent subtitles instead of guessing. Tie each result to a timestamp, stream index, subtitle range or source hash.
When to use it
Useful when an assistant needs to answer questions about a local video file, such as which chapter covers a topic, where a quote appears, or what a frame at a given moment shows, and should cite timestamps rather than invent a transcript.
Requirements
Runs as a local stdio process, started with npx from the npm package @sylphx/cue. Needs local video files by absolute path and ffprobe for metadata; no cloud video API, account, API key or environment variable is declared.
Before you install
The repository is archived and the project was merged into another tool, so it may not be maintained. Speech recognition is not performed and quote search only matches embedded subtitles, so results can be empty. Scene, frame and transcript options are limited: keyframes and transcripts return a warning and empty array, and OCR runs only through the evidence tool.

Installation

In SourceWeft

  1. Open Cue in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

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

Source: README.md at commit 30773b7

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

4
  1. v0.3.5LatestSep 23, 2026
  2. v0.3.4Sep 23, 2026
  3. v0.3.3Sep 23, 2026
  4. v0.3.2Sep 23, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts