Upload a video from a URL. Returns a video_id. Local file paths are not accepted; upload files outside the MCP server and pass a reachable video_url. The upload runs asynchronously — poll get_video until status is 'uploaded', then call index_video to enable search and analysis.

List all videos in your account, or filter to a specific group by passing group_id. Shows upload status and which features have been indexed for each video. Each video's 'url' is a short-lived HTTPS presigned URL (expires within hours) — fetch immediately and do not store; call list_videos or get_video again for a fresh URL when needed.

Get detailed information about a video including upload status, metadata (duration, resolution, fps), and per-feature indexing status. Use this to check if upload or indexing is complete. The 'url' field is a short-lived HTTPS presigned URL (expires within hours) — fetch immediately and do not store; call get_video again for a fresh URL when needed.

Update a video's display name, title, description, or move it to a different group. At least one field must be provided. To remove a video from its group, pass group_id as null.

Permanently delete a video and all its indexed data (transcript, captions, embeddings, etc.). This cannot be undone.

Create a new video group. Groups organize videos into collections. Returns the new group's ID and name.

List all video groups. Use list_videos with a group_id to see videos in a specific group.

Delete a video group. Videos in the group are not deleted — they are simply removed from the group.

Index a video for search, QA, or full analysis. Processes the video through a pipeline of AI features. Typically takes 3-7 minutes; longer for long videos or the 'full' pipeline. Times out after 10 minutes by default.

Pipelines:

• search_only: transcription + captions + embeddings (enables search_videos)

• qa_only: transcription + captions (enables ask_video)

• full: transcription + captions + embeddings (enables all tools)

Scene detection is enabled by default and produces scene boundaries for get_scenes. Pass scene_detection=False to skip it.

Prerequisites: if using video_id, the video must be in 'uploaded' status. Use get_video to check status before calling this tool.

Accepts either video_id (for an already-uploaded video) or file_path (a local file to upload and index in one step). Provide exactly one.

Find WHEN and WHERE something happens across your videos. Returns timestamped results ranked by relevance — use these timestamps as start/end in ask_video for focused analysis.

This is the recommended first step for most questions. Instead of asking ask_video about the entire video, search first to narrow down the relevant moments.

Each result's 'video_url' is a short-lived HTTPS presigned URL (expires within hours) — fetch immediately and do not store; call search_videos or get_video again for a fresh URL when needed.

Requires search_only or full pipeline.

Ask a question about one or more videos with visual analysis. Most effective on focused time ranges — use start/end to specify the segment to analyze.

BEFORE calling this tool, read the reka://docs/guide resource for recommended workflows. In most cases, you should first:

• search_videos to find WHEN something happens, then pass those timestamps here as start/end

• segment_video to detect and locate specific objects

• get_transcript to read what was said

For single-video questions, pass video_id with start/end. For cross-video questions, pass videos — a list of video references with start/end each.

For follow-up questions, pass conversation_id from the previous response. You can add start/end to drill into a specific moment while keeping the conversation context.

Requires qa_only or full pipeline.

Detect objects in a video segment using text prompts. Describe what to look for and get per-frame detections with bounding boxes and confidence scores.

Prompt tips:

• Use broad, visual categories: 'animal', 'vehicle', 'person', 'text on screen'

• Specific labels ('rabbit', 'Toyota') are less reliable — the detector matches visual patterns, not semantic concepts

• Best for confirming whether a category of object appears in a time window, not for precise identification

How to pick a time range:

• Use search_videos to find WHEN something appears, then pass those timestamps here

• Use get_scenes to scan systematically — call segment_video once per scene (scenes typically fit in the 15s window)

• Or pass any range you already know

Maximum range is 15 seconds per call; for longer spans, make multiple calls with consecutive windows.

Does NOT require any feature indexing — works on any uploaded video.

Get the spoken words in a video. Use this instead of ask_video when you need to read what was said — it returns the actual text, not a summary.

Use start/end to narrow results for long videos.

Requires the transcript feature to be indexed.

Get AI-generated visual descriptions of what happens on screen. Use this to understand the visual content without watching — each caption describes a short segment with timestamps.

Use start/end to narrow results.

Requires the captions feature (qa_only or full pipeline).

Get detected scene boundaries with start/end timestamps. Use this to understand the video's structure, then pass scene timestamps as start/end to:

• ask_video for per-scene contextual analysis

• segment_video to detect specific objects per scene (scenes typically fit in segment_video's 15s max range)

Requires transcript indexed with scene detection (on by default; skipped only if index_video was called with scene_detection=False).

List available video analysis features with their dependencies and descriptions. Use this to understand what features exist and what pipelines to use with index_video.

Start here. Get a compact overview of a video: metadata, which features are indexed, a transcript preview, and scene count. Use this to decide which tools to call next — then use segment_video to detect specific objects in time ranges of interest.