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spxrtiat111

2Sense

by spxrtiat111
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GROQ_API_KEYYesYour free Groq API key

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
transcribeA

Transcribe speech from a local audio OR video file using Groq Whisper.

Args:
    path: Absolute path to an audio or video file (video audio is auto-extracted).
    language: "auto" to detect, or an ISO code like "fr" / "en" to force.

Returns: {text, language, duration, segments:[{start,end,text}]}.
audio_profileA

Analyze music/energy/rhythm of an audio OR video file (free, local, numpy-based).

Returns tempo (BPM), energy curve, onset 'hits' (useful vs. visual cuts), loudness dynamics, brightness, and a music-vs-speech estimate. No genre/mood/song-ID.

audio_eventsA

Tag audio events with YAMNet (free, local): Music, Speech, instruments, genres, SFX (whoosh/beep/...). Works on an audio OR video file.

Returns {top:[{label,score}], rollup:{Music,Speech,SFX}, timeline:[{start,end,label}]}.
No mood (happy/sad) — YAMNet covers events/instruments/genres, not affect.
analyze_adA

Give Claude EYES + EARS on a short-form video ad.

Runs the local prep pipeline (download if a URL, sample frames at the configured
fps, tile them into labeled contact sheets, extract audio), transcribes the audio,
and returns: a text block (timestamp legend + transcript) followed by the contact
sheet IMAGES. Look at the images and read the transcript to analyze the ad.

Args:
    source: A local video path OR a TikTok / Reels / YouTube / Meta URL.
    language: "auto", or an ISO code like "fr" / "en" to force transcription language.
    with_audio: set false to skip transcription (eyes only).

Returns: [text, image, image, ...] — contact sheets each have per-cell timestamps
burned into the top-left as `t=SECONDS`, matching the legend in the text block.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.9/5.0

Scored across 4 tools

Disambiguation4/5

Tools have largely distinct purposes: analyze_ad combines visual and audio ad analysis, audio_events focuses on event detection, audio_profile on musical attributes, and transcribe on speech transcription. Some overlap exists (analyze_ad includes transcription), but descriptions clarify boundaries.

Naming Consistency2/5

Naming is inconsistent: analyze_ad uses verb_noun with underscore, audio_events and audio_profile use noun_noun, and transcribe is a single verb. No consistent pattern emerges.

Tool Count4/5

With 4 tools, the set is slightly lean but covers essential analysis tasks for audio/video. Each tool serves a clear purpose, though there is room for additional utilities.

Completeness4/5

The tool surface covers core ad analysis (visual frames, transcription, audio events, music profiling). Missing features like emotional analysis or speaker identification are minor gaps not critical for the primary use case.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources