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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
GEMINI_API_KEYYesYour Gemini API key from Google AI Studio
IMAGE_OUTPUT_DIRNoWhere to save generated images~/banana-images

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

Tools

Functions exposed to the LLM to take actions

NameDescription
generate_imageA

Generate new images or edit existing images using natural language instructions.

Supports multiple input modes:

  1. Pure generation: Just provide a prompt to create new images

  2. Multi-image conditioning: Provide up to 3 input images using input_image_path_1/2/3 parameters

  3. File ID editing: Edit previously uploaded images using Files API ID

  4. File path editing: Edit local images by providing single input image path

Automatically detects mode based on parameters or can be explicitly controlled. Input images are read from the local filesystem to avoid massive token usage. Returns both MCP image content blocks and structured JSON with metadata.

upload_fileA

Upload a local file through the Gemini Files API and return its URI & metadata. Useful when the image is larger than 20MB or reused across prompts.

show_output_statsA

Show statistics about the output directory and recently generated images.

maintenanceB

Perform maintenance operations following workflows.md patterns.

Available operations:

  • cleanup_expired: Remove expired Files API entries from database

  • cleanup_local: Clean old local files based on age/LRU

  • check_quota: Check Files API storage usage vs. ~20GB budget

  • database_hygiene: Clean up database inconsistencies

  • full_cleanup: Run all cleanup operations in sequence

Prompts

Interactive templates invoked by user choice

NameDescription
photorealistic_shotGenerate a prompt for high-quality photorealistic images.
logo_textGenerate a prompt for logo creation with accurate text rendering.
product_shotGenerate a prompt for studio product photography.
sticker_flatGenerate a prompt for flat/kawaii style stickers.
iterative_edit_instructionGenerate an instruction for precise image editing.
composition_and_style_transferGenerate an instruction for style transfer and composition blending.

Resources

Contextual data attached and managed by the client

NameDescription
prompt_templates_catalogA compact catalog of prompt templates (same schemas as the @mcp.prompt items).
list_operationsList all tracked operations. Returns: Dict with list of operations and summary statistics

TDQS

A3.9/5.0

Scored across 4 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: generate_image for creating/editing images, maintenance for system cleanups, show_output_stats for monitoring, and upload_file for file uploads. There is no ambiguity between them.

Naming Consistency4/5

Most tool names follow a verb_noun pattern (generate_image, show_output_stats, upload_file). 'Maintenance' is a single noun but still clear and fits the overall style. Minor inconsistency does not cause confusion.

Tool Count5/5

Four tools is well-scoped for an image generation server. Each tool addresses a key aspect: generation, upload, maintenance, and statistics. The count is neither too few nor excessive.

Completeness4/5

The tools cover core image operations (generation, upload, maintenance, stats). A minor gap is the lack of a dedicated delete tool for images, but maintenance can clean up expired files, so it's workable.

Maintenance

ActivityInactive
ResponsivenessNo issues