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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GEMINI_API_KEYYesGemini API key, required
VEO_OUTPUT_DIRNoWhere videos are saved./veo
VEO_TIMEOUT_MSNoWhen to give up on a render900000
VEO_POLL_INTERVAL_MSNoHow often to poll the render10000

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": true
}

Tools

Functions exposed to the LLM to take actions

NameDescription
generate_videoA

Generate a video from a text prompt with Google Veo, optionally starting from an image (image-to-video) and ending on another one. Paid per second of video and takes 1-5 minutes, so ask before generating several variants. Saves an MP4 to disk and returns its path.

fetch_videoA

Wait for an already started Veo operation and save its video. Use it when generate_video failed after the render had started: its error names the operation. Costs nothing extra.

list_modelsA

List Veo model ids available to this API key.

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 3 tools

Disambiguation5/5

Each tool has a clearly distinct role: list_models discovers model ids, generate_video starts a paid render, and fetch_video recovers an already-started operation. The descriptions explicitly distinguish starting a new render from fetching an existing one.

Naming Consistency5/5

All three tools follow a consistent snake_case verb_noun pattern: list_models, generate_video, fetch_video. There is no mixing of conventions or vague standalone verbs.

Tool Count5/5

Three tools is a tight, well-scoped surface for a video-generation server: discovery, generation, and recovery are each covered without redundancy. No tool feels extraneous.

Completeness4/5

The core workflow is covered: list available models, generate text/image-to-video, and fetch a video from a started operation. Minor gaps exist around operation management, such as checking status without fetching or cancelling a render, but these are not critical for the stated use case.

Maintenance

ActivityMaintained
ResponsivenessUnresponsive