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Glama
ivanantigravity-lgtm

GPT Image 2 Polza MCP Server

by ivanantigravity-lgtm
OverviewSchemaSourceRelated ServersScoreDiscussionsAdmin
Python
Remote

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
POLZA_BASE_URLNoБазовый URL API; по умолчанию https://polza.ai/apihttps://polza.ai/api
GPT_IMAGE_MODELNoModel tier; по умолчанию gpt-image-2gpt-image-2
IMAGE_OUTPUT_DIRNoПапка результатов; по умолчанию ~/gpt-image-2-images~/gpt-image-2-images
POLZA_AI_API_KEYYesAPI-ключ аккаунта Polza
RETURN_FULL_IMAGENoВозвращать полное изображение вместо превью
POLZA_EXTERNAL_USER_IDNoВнешний ID пользователя для Polza
POLZA_POLL_TIMEOUT_SECONDSNoМаксимальное время ожидания результата
POLZA_POLL_INTERVAL_SECONDSNoИнтервал проверки статуса генерации

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
{
  "tasks": {
    "list": {},
    "cancel": {},
    "requests": {
      "tools": {
        "call": {}
      },
      "prompts": {
        "get": {}
      },
      "resources": {
        "read": {}
      }
    }
  }
}

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 Polza Storage 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

fetch_generationD–

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