A
licenseB
qualityA
maintenanceEnables AI image and video generation tasks (text-to-image, image-to-video, edit, upscale, etc.) via RunAPI, with support for polling and pricing lookups.
10
282 npm
1
Apache 2.0
z-image-mcp
by runapi-ai
Related Servers
Alternatives to z-image-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityBmaintenanceEnables creating and managing GPT Image tasks (edit and text-to-image) via RunAPI, with options to poll status and check pricing.5293 npmApache 2.0
- AlicenseAqualityBmaintenanceEnables image editing, remixing, and text-to-image generation using Qwen 2 models via RunAPI. Supports task polling and pricing checks.5260 npmApache 2.0
- AlicenseBqualityBmaintenanceEnables background removal and upscaling of images using Recraft models via RunAPI, with task polling and pricing lookup.5240 npmApache 2.0
- FlicenseNot gradedqualityAmaintenanceEnables AI agents to generate images from text prompts via Z-Image-Turbo, list available models, and view generation history over stdio, SSE, or Streamable HTTP transports.-
Runway API MCP Serverofficial
AlicenseAqualityFmaintenanceEnables AI video and image generation through the Runway API. Supports video generation from images and text prompts, image creation, video upscaling and editing, and task management.712 npm23MIT
TDQS
A3.5/5.0
Scored across 4 tools
Disambiguation5/5
Each tool targets a clearly distinct concern: authentication (login), task creation (text_to_image), task polling (get_task), and pricing lookup (check_pricing). No two tools could plausibly be confused for one another.
Naming Consistency4/5
Three tools follow a readable verb/noun style (get_task, check_pricing, text_to_image) while 'login' is a bare verb, a minor deviation. The overall pattern is predictable enough that an agent can infer intent from names alone.
Tool Count4/5
Four tools is a lean but coherent minimum for a single-model image generation service: authenticate, generate, poll, check cost. It is slightly thin but nothing feels redundant or padded.
Completeness3/5
The core create-then-poll lifecycle is covered, but there is no cancel/delete task, no list-tasks operation, and no image-to-image or edit variant for what is presumably an image model. Agents can work around these gaps but will hit dead ends for anything beyond basic text-to-image generation.
Maintenance
ActivityMaintained
ResponsivenessNo issues