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ilovevideoeditor

ilovevideoeditor

Local
github.com/ilovevideoeditorMedia & Design0Updated 15w ago
Repository

About ilovevideoeditor

ilovevideoeditor is an MCP server for AI agents to create MP4 videos from JSON or motion-design templates. It supports template discovery, render tracking, and download links.

Key features

  1. 01List templates and inspect variables
  2. 02Render JSON or template-based videos
  3. 03Check render job status
  4. 04Retrieve signed download URLs

Use cases

  1. 01Create videos from structured JSON
  2. 02Render videos using reusable templates
  3. 03Track rendering and retrieve finished files

MCP support

Exposes tools to MCP clients for listing templates, submitting JSON or template-based render jobs, checking status, and retrieving download URLs.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "ilovevideoeditor": {
      "command": "npx",
      "args": [
        "-y",
        "@ilovevideoeditor/mcp-server"
      ],
      "env": {
        "VF_API_KEY": "<VF_API_KEY>",
        "VF_API_BASE_URL": "<VF_API_BASE_URL>"
      }
    }
  }
}
Run commandnpx -y @ilovevideoeditor/mcp-server
Environment variables to set
VF_API_KEYSecretiLoveVideoEditor API key (generate at ilovevideoeditor.com/dashboard/account/api)
VF_API_BASE_URLAPI base URL override

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@ilovevideoeditor/mcp-server1.0.0

Tools

10

Saved tool list · updated 2w ago

This tool takes no parameters.

Details

From the project README

iLoveVideoEditor MCP Server

Model Context Protocol (MCP) server that lets AI agents (Claude, ChatGPT, Cursor, and any MCP client) render videos with iLoveVideoEditor: list motion-design templates, fill in variables, submit JSON-to-MP4 render jobs, poll status, and get download URLs.

Quick start

Get an API key from the dashboard: ilovevideoeditor.com/dashboard/account/api

Add the server to your MCP client config:

{
  "mcpServers": {
    "ilovevideoeditor": {
      "command": "npx",
      "args": ["-y", "@ilovevideoeditor/mcp-server"],
      "env": {
        "VF_API_KEY": "vf_live_xxx"
      }
    }
  }
}

Tools

ToolDescription
ilovevideoeditor_list_templatesList available templates
ilovevideoeditor_get_templateGet template details and variable schema
ilovevideoeditor_render_jsonSubmit raw VideoJSON for rendering
ilovevideoeditor_render_templateRender from a named template + variables
ilovevideoeditor_get_render_statusPoll render job status
ilovevideoeditor_get_download_urlGet signed download URL

Configuration

VariableDefaultDescription
VF_API_KEY—Required. Your iLoveVideoEditor API key (x-api-key)
VF_API_BASE_URLhttps://api.ilovevideoeditor.comAPI base URL override

Development

npm install
npm run build    # tsc -> dist/
npm start        # stdio transport
npm run dev      # tsx watch

The server speaks MCP over stdio (diagnostics go to stderr). An optional --http flag enables HTTP/SSE transport for debugging.

Source of truth lives in the iLoveVideoEditor monorepo (integrations/mcp-server); this repository is the public mirror used for releases.

License

Apache-2.0

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.