Reka
Understand your videos with Reka AI — search, ask questions, and extract insights.
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Understand your videos with Reka AI — search, ask questions, and extract insights.
Список инструментов сервера (17)
Технические названия из tools/list. Нужны только разработчикам.
| upload_video | 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_videos | 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_video | 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_video | 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. |
| delete_video | Permanently delete a video and all its indexed data (transcript, captions, embeddings, etc.). This cannot be undone. |
| create_group | Create a new video group. Groups organize videos into collections. Returns the new group's ID and name. |
| list_groups | List all video groups. Use list_videos with a group_id to see videos in a specific group. |
| delete_group | Delete a video group. Videos in the group are not deleted — they are simply removed from the group. |
| index_video | 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. |
| search_videos | 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_video | 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. |
| segment_video | 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_transcript | 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_captions | 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_scenes | 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). |
| get_feature_catalog | 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. |
| summarize_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. |