Ghibli Video MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| Ghibli_API_URL | No | The API URL for the GPT4O Image Generator service | https://www.gpt4oimg.com |
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| image_to_videoC | Convert image to animated video |
| get_pointsC | Get remaining points |
| get_task_resultC | Get task result |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose with no overlap: get_points retrieves points, get_task_result fetches task results, and image_to_video handles video conversion. An agent can easily differentiate them based on their specific functions.
The tools follow a consistent verb_noun pattern (get_points, get_task_result, image_to_video), with minor deviations in verb usage (get vs. image_to). The naming is readable and mostly predictable, though not perfectly uniform.
With only 3 tools, the set feels thin for a video server's apparent scope, lacking operations like video management, task creation, or point usage. This minimal count may limit agent workflows and indicate incomplete coverage.
There are significant gaps in the tool surface for a video server domain: no tools for creating tasks, managing videos, or using points, and core operations like video playback or editing are missing. This will likely cause agent failures in handling typical video-related workflows.