What is A Model Context Protocol (MCP) server for generating videos using the json2video API.?
This server exposes powerful video generation and status-checking tools for use with LLMs, agents, or any MCP-compatible client. It supports rich scene and element configurations, asynchronous rendering, and API key authentication.
Documentation
json2video MCP Server
A Model Context Protocol (MCP) server implementation for programmatically generating videos using the json2video API. This server exposes powerful video generation and status-checking tools for use with LLMs, agents, or any MCP-compatible client.
Features
Generate videos with rich scene and element support (text, image, video, audio, components, subtitles, etc.)
Asynchronous video rendering with status polling
Flexible, extensible JSON schema for video projects
Designed for easy integration with LLMs, automation agents, and MCP-compatible tools
Replace your_api_key_here with your json2video API key. You can get an API key from json2video.com.
After adding, refresh the MCP server list to see the new tools. Your agent or LLM will automatically use json2video MCP when appropriate, or you can explicitly request it by describing your video generation needs.
Replace your_api_key_here with your actual json2video API key.
This configuration allows your agent or LLM to start and communicate with the json2video MCP server automatically.
The server will expose the generate_video and get_video_status tools for use in your workflows.
Configuration# Environment Variables
JSON2VIDEO_API_KEY (required): Your json2video API key. Can be set as an environment variable or provided per request.
Note: If you encounter a client closed error, run the following command in your terminal:
npm i @omerrgocmen/json2video-mcp
Usage# Available Tools
1. Generate Video (generate_video)
Create a customizable video project with scenes and elements.
Description:
Creates a video project using the json2video API. Each project can contain multiple scenes, and each scene can contain various elements such as text, images, video, audio, components, HTML, voice, audiogram, and subtitles. Video generation is asynchronous; use the returned project ID to check status. See https://json2video.com/docs/api/ for full schema and more examples.
Input Schema:
{
"id": "string (optional, unique identifier for the movie)",
"comment": "string (optional, project description)",
"cache": true,
"client_data": {},
"draft": true,
"quality": "high", // one of: low, medium, high
"resolution": "custom", // one of: sd, hd, full-hd, squared, instagram-story, instagram-feed, twitter-landscape, twitter-portrait, custom
"width": 1920, // required if resolution is custom
"height": 1080, // required if resolution is custom
"variables": {},
"elements": [ /* global elements, see below for examples */ ],
"scenes": [
{
"id": "string (optional, unique scene id)",
"comment": "string (optional)",
"background_color": "#000000",
"cache": true,
"condition": "string (optional)",
"duration": -1,
"variables": {},
"elements": [ /* see element examples below */ ]
}
],
"apiKey": "string (optional)"
}
You can mix and match element types in scenes and globally.
For custom resolutions, set both width and height.
Use the returned project ID to check video status with get_video_status.
Output:
Returns a project ID to be used with get_video_status.
2. Get Video Status (get_video_status)
Check the status or retrieve the result of a video generation job.
Description:
Retrieves the status or result of a previously started video generation job. Note: Video rendering is asynchronous and may take some time. If the status is not "done", please try again later using the same project ID.