image2video

mcphub-com/image2video

4.6

image2video is hosted online, so all tools can be tested directly either in theInspector tabor in theOnline Client.

If you are the rightful owner of image2video and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

The Image-to-Video MCP is a service that transforms static images into dynamic videos using textual guidance.

Try image2video with chat:

Server config via mcphub

Traditional api access examples

Path-based authentication

Tools
2
Resources
0
Prompts
0

Image-to-Video MCP

Overview

The Image-to-Video MCP (Model Context Protocol) provides a powerful tool for generating videos from static images with textual guidance. This service utilizes advanced AI models to transform static imagery into dynamic video content based on textual prompts, enabling seamless integration of image-to-video generation capabilities into various applications.

Key Features

  • Image-to-Video Conversion: Transform static images into dynamic videos with motion effects
  • Text-Guided Generation: Use textual prompts to guide the transformation process and desired effects
  • Task Management System: Unique task IDs for tracking generation progress and retrieving results

API Specification

image2video_submit_task Tool

@mcp.tool()
async def image2video_submit_task(
    image: Annotated[str, Field(
        description="the url of image you want to transform to video")],
    prompt: Annotated[str, Field(description="prompt of the transform you want to achieve.")]
):
    """submit a task to transform one image to video and get task_id."""
Parameters
  • image (string, required): The URL of the source image that will be transformed into a video. The image should be accessible via HTTP/HTTPS.
  • prompt (string, required): The textual description guiding the transformation process, specifying the desired motion, effects, or style changes.
Returns

The tool returns a task ID that can be used to check the status and retrieve results once the video generation is complete. The response typically includes:

  • Task ID for future reference

image2video_check_task Tool

@mcp.tool()
async def image2video_check_task(
    task_id: Annotated[str, Field(
        description="check if the task you have submited is finished and fetch the result.")]
):
    """use the task_id to check the status of task and try fetch result."""
Parameters
  • task_id (string, required): The unique identifier received when submitting an image-to-video transformation task.
Returns

The tool returns the current status of the task and, if completed, the result of the video generation. Possible responses include:

  • Processing status with progress information
  • Completion status with a URL to the generated video
  • Error information if the task failed

Workflow Integration

Typical Usage Pattern

  1. Task Submission: Client applications submit an image URL and transformation prompt using image2video_submit_task
  2. Task Tracking: The service returns a unique task ID for tracking the generation process
  3. Status Checking: Clients periodically check task status using image2video_check_task with the provided task ID
  4. Result Retrieval: Once processing is complete, clients retrieve the URL of the generated video

Performance Considerations

  • Video generation is computationally intensive and may take several minutes to complete
  • The service implements an asynchronous task queue to handle multiple requests efficiently
  • For high-volume applications, consider implementing client-side caching of generated videos