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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

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
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
popcorn_suggestA

Probe a video file and get suggested analysis settings. Returns video metadata, suggested video type, and recommended presets. Use this FIRST to understand the video and choose appropriate settings before running popcorn_analyze.

popcorn_presetsA

List all available video type presets and objectives. Use this to understand what options are available for popcorn_analyze.

popcorn_analyzeA

Analyze a video file. Extracts keyframes and transcripts. RECOMMENDED: First use popcorn_suggest to get optimal settings, or specify videoType and objective to use smart presets.

popcorn_readA

Read a file from an analysis bundle with optional line slicing or transcript time filtering.

popcorn_backendsA

List available transcription backends on this system. Shows which backends are installed and ready to use. Use this to help users choose the best transcription option.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.2/5.0

Scored across 5 tools

Disambiguation5/5

Each tool has a clear, distinct purpose: suggest probes and recommends settings, presets lists options, analyze performs the analysis, read accesses results, and backends shows system capabilities. No two tools appear to do the same thing.

Naming Consistency4/5

All tools share a consistent popcorn_ prefix, but the suffix style mixes verbs (suggest, analyze, read) with nouns (presets, backends). This is a minor deviation from a uniform verb_noun pattern, but the names are still predictable and readable.

Tool Count5/5

With 5 tools, the set is well-scoped for video analysis. Each tool covers a distinct step in the workflow (probe, list options, analyze, read output, check backends), earning its place without redundancy.

Completeness5/5

The tool surface provides a complete workflow: suggest gives metadata and recommended settings, analyze runs the analysis, and read retrieves results. Presets and backends offer configuration information. No critical operations are missing for the stated purpose.

Maintenance

ActivityInactive
ResponsivenessNo issues