video-vision-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| JIRA_URL | No | Jira instance URL (optional, for analyzing Jira attachments). | |
| GROQ_API_KEY | No | Groq API key for tier 2 (cloud ASR). Optional, but if set, transcription uses Groq. | |
| JIRA_USERNAME | No | Jira username or email (optional). | |
| VIDEO_MCP_ENV | No | Path to a .env file to load environment variables. | |
| GEMINI_API_KEY | No | Gemini API key for tier 3 (native Gemini analysis). Optional, but if set, it becomes the default backend (unless disabled by VIDEO_MCP_DISABLE_GEMINI). | |
| JIRA_API_TOKEN | No | Jira API token (optional). | |
| OPENAI_API_KEY | No | OpenAI API key for tier 2 (cloud ASR). Optional, but if set, transcription uses OpenAI Whisper. | |
| VIDEO_MCP_CACHE_DIR | No | Override the default cache directory (~/.cache/video-vision-mcp/). | |
| VIDEO_MCP_WHISPER_MODEL | No | Whisper model to use for local transcription (tiny/base/small/medium/large-v3). Default: base. | |
| VIDEO_MCP_DISABLE_GEMINI | No | Set to 'true' to disable Gemini even if GEMINI_API_KEY is set, forcing tiers 1/2. | |
| VIDEO_MCP_WHISPER_MODEL_PATH | No | Path to a custom whisper model file (overrides VIDEO_MCP_WHISPER_MODEL). |
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_videoA | Analyze a video into frames + transcript + metadata. Provide exactly ONE source:
frame_interval: seconds between sampled frames (default 1.0 = one per second). Denser sampling: 0.5 / 0.25 / 0.1; sparser: 2 / 5; or any custom value. The total is capped by the frame budget so long/dense videos can't flood context. Ignored by the native Gemini backend (it ingests the whole video). The backend (local whisper.cpp / OpenAI / Groq / native Gemini) is chosen automatically from configured keys and named in the result metadata. Results are cached per (file-hash, backend, frame_interval); pass force_refresh=true to recompute. |
| get_video_transcript_onlyC | Fast path: return only the transcript text (no frame images). Same inputs and backend selection as analyze_video. With the Gemini backend, returns Gemini's analysis text instead of a plain transcript. |
| extract_frames_atA | Extract frames at specific timestamps. timestamps accepts seconds ("12", "12.5") or "MM:SS" / "HH:MM:SS". Tier 1/2 return real frame images; with the Gemini backend you get a textual description of those moments instead (no local frame cutting). |
| list_recent_analysesA | List previously analyzed videos from the cache, with the backend used for each. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
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