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KitDevUA

video-vision-mcp

by KitDevUA
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
JIRA_URLNoJira instance URL (optional, for analyzing Jira attachments).
GROQ_API_KEYNoGroq API key for tier 2 (cloud ASR). Optional, but if set, transcription uses Groq.
JIRA_USERNAMENoJira username or email (optional).
VIDEO_MCP_ENVNoPath to a .env file to load environment variables.
GEMINI_API_KEYNoGemini 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_TOKENNoJira API token (optional).
OPENAI_API_KEYNoOpenAI API key for tier 2 (cloud ASR). Optional, but if set, transcription uses OpenAI Whisper.
VIDEO_MCP_CACHE_DIRNoOverride the default cache directory (~/.cache/video-vision-mcp/).
VIDEO_MCP_WHISPER_MODELNoWhisper model to use for local transcription (tiny/base/small/medium/large-v3). Default: base.
VIDEO_MCP_DISABLE_GEMININoSet to 'true' to disable Gemini even if GEMINI_API_KEY is set, forcing tiers 1/2.
VIDEO_MCP_WHISPER_MODEL_PATHNoPath to a custom whisper model file (overrides VIDEO_MCP_WHISPER_MODEL).

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
analyze_videoA

Analyze a video into frames + transcript + metadata.

Provide exactly ONE source:

  • file_path: local path to a video file (already on disk).

  • url: direct/streaming URL (yt-dlp for known sites, HTTP otherwise).

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

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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