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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GEMINI_API_KEYYesAPI key from a Google Cloud project with billing enabled (Gemini API Free Tier does NOT support image generation models).

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
nanobanana_generate_imageA

Generate an image using Gemini's native image generation (Nano Banana).

This tool calls the Gemini API to generate an image based on your text prompt and saves it to the specified path.

Models:

  • gemini-2.5-flash-image: Fast, efficient (~$0.039/image)

  • gemini-3-pro-image-preview: Higher quality, supports 4K (~$0.134-0.24/image)

Supported Aspect Ratios: 1:1, 16:9, 9:16, 4:3, 3:4

Example:

prompt: "A modern flat illustration of a workflow diagram with three connected nodes, purple and blue gradient colors, minimal style"
output_path: "assets/generated/workflow-hero.png"
model: "gemini-2.5-flash-image"
aspect_ratio: "16:9"
nanobanana_list_queueA

List and validate prompt files in the queue directory.

This tool scans the queue directory for markdown prompt files and provides:

  • Validation status for each file

  • Conflict detection (output file already exists)

  • Preview of prompt content

Use this to review what will be generated before running process_queue.

Example:

queue_dir: "nanobanana/queue"
validate: true
check_conflicts: true
nanobanana_process_queueA

Process all prompt files in the queue directory and generate images.

Modes:

  • validate_only=true: Only validate prompts, no API calls

  • dry_run=true: Show what would be generated, no API calls

  • Both false: Actually generate images

Overwrite Strategies:

  • skip: Skip if output file exists (default)

  • overwrite: Replace existing files

  • rename: Generate with suffix (e.g., hero_1.png)

After successful generation, prompt files are moved to completed_dir with timestamp.

Example:

queue_dir: "nanobanana/queue"
dry_run: true
overwrite: "skip"

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.3/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose with no overlap: generate_image creates individual images, list_queue inspects pending files, and process_queue batch processes the queue. The descriptions reinforce these separate functions, making misselection unlikely.

Naming Consistency5/5

All tools follow a perfect verb_noun pattern with the 'nanobanana_' prefix: generate_image, list_queue, process_queue. This consistent naming convention makes the tool set predictable and easy to understand.

Tool Count5/5

Three tools is ideal for this server's focused scope of image generation queue management. Each tool earns its place by covering distinct aspects of the workflow: single generation, queue inspection, and batch processing.

Completeness4/5

The tool set covers the core image generation workflow well with generation, inspection, and processing capabilities. A minor gap exists in not providing tools for managing completed images or modifying queue entries, but agents can work around this with file system operations.