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Glama
AceDataCloud

WanMCP

by AceDataCloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
LOG_LEVELNoLogging levelINFO
WAN_DEFAULT_MODELNoDefault video modelwan2.6-t2v
WAN_REQUEST_TIMEOUTNoRequest timeout in seconds1800
ACEDATACLOUD_API_TOKENYesAPI token from AceDataCloud
WAN_DEFAULT_RESOLUTIONNoDefault resolution720P
ACEDATACLOUD_API_BASE_URLNoAPI base URLhttps://api.acedata.cloud

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

Tools

Functions exposed to the LLM to take actions

NameDescription
wan_list_modelsA

List all available Wan video generation models.

Shows models with their capabilities, supported actions, and use cases.

Returns:
    Table of all models with descriptions and constraints.
wan_list_resolutionsA

List all available resolutions for Wan video generation.

Shows resolution options with their quality and use cases.

Returns:
    Table of resolutions with descriptions.
wan_list_actionsA

List all available Wan API actions and corresponding tools.

Reference guide for what each action does and which tool to use.

Returns:
    Categorized list of all actions and their corresponding tools.
wan_get_taskA

Query the status and result of a video generation task.

Use this to check if a generation is complete and retrieve the resulting
video URLs and metadata.

Task states:
- 'pending': Generation is queued
- 'processing': Generation is in progress
- 'completed': Generation finished successfully
- 'failed': Generation failed (check error message)

Returns:
    Task status and generated video information including URLs.
wan_get_tasks_batchA

Query multiple video generation tasks at once.

Efficiently check the status of multiple tasks in a single request.

Returns:
    Status and video information for all queried tasks.
wan_generate_videoA

Generate AI video from a text prompt using Wan text-to-video model.

This uses the wan2.6-t2v model to create video from text descriptions.
For creating video from images, use wan_generate_video_from_image instead.

Returns:
    Task ID and generated video information including URLs and state.
wan_generate_video_from_imageA

Generate AI video from a reference image using Wan image-to-video models.

This supports three models:
- wan2.6-i2v: Standard image-to-video generation
- wan2.6-r2v: Reference video-to-video with character/timbre extraction
- wan2.6-i2v-flash: Fast image-to-video generation

Returns:
    Task ID and generated video information including URLs and state.

Prompts

Interactive templates invoked by user choice

NameDescription
wan_video_generation_guideGuide for choosing the right Wan tool for video generation.
wan_workflow_examplesCommon workflow examples for Wan video generation.
wan_prompt_suggestionsPrompt writing suggestions for Wan video generation.

Resources

Contextual data attached and managed by the client

NameDescription

No resources

Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.2/5.0

Scored across 7 tools

Disambiguation5/5

Each tool targets a distinct operation: three list endpoints for different reference data, two task-query endpoints (single vs. batch), and two generation endpoints (text-to-video vs. image-to-video). Descriptions clearly indicate when to use which tool.

Naming Consistency5/5

All tools follow a consistent wan_ prefix with a verb_noun pattern (list_*, get_*, generate_*). The naming is predictable and clearly indicates the action and subject.

Tool Count5/5

Seven tools is well-scoped for a video generation MCP server. Each tool serves a necessary purpose, and the set is not bloated or sparse.

Completeness4/5

The core workflow of listing capabilities, generating video, and querying results is fully covered. Minor gaps include no cancel-task operation and no list-all-tasks endpoint, but these do not severely impact typical usage.

Maintenance

ActivitySlowing
ResponsivenessUnresponsive

Resources