MCP Server

MCP server for Luma Dream Machine AI video generation

Remote serverstreamable-httpPython

What is the MCP MCP server?

MCP MCP server exists for a simple reason — assistants are far more useful when they can act on MCP directly instead of describing what you should do. MCP server for Luma Dream Machine AI video generation.

What you get

Generate AI videos directly from Claude, VS Code, or any MCP-compatible client.

  • Text to Video — - Create AI-generated videos from text prompts
  • Image to Video — - Animate images with start/end frame control
  • Video Extension — - Extend existing videos with additional content
  • Multiple Aspect Ratios — - Support for 16:9, 9:16, 1:1, and more
  • Loop Videos — - Create seamlessly looping animations
  • Clarity Enhancement — - Optional video quality enhancement

Setting it up

Being a remote server, there is no local install. You register the endpoint with your client, authorise it once, and the tools appear.

What the assistant can call

Once MCP is connected, these are the calls the assistant has available:

  • Cline — The Cline tool exposed by this server
  • Tasks — The Tasks tool exposed by this server
  • Information — The Information tool exposed by this server

Configuration and credentials

You will need 5 environment variables: ACEDATACLOUD_API_TOKEN, YOUR_API_TOKEN, ACEDATACLOUD_API_BASE_URL, ACEDATACLOUD_OAUTH_CLIENT_ID, ACEDATACLOUD_PLATFORM_BASE_URL. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.

Before you rely on it

  • Your data travels to the provider's service, so the usual questions apply about what you send and what they retain.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • MCP clients confirm each tool call by default. Leave that on until you have watched what the mcp mcp server does with a few real requests.

Choosing this one

Among the planning and project tracking options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. MCP's toolset — Cline, Tasks, Information — is a fair guide to whether it matches your workflow. It is maintained by AceDataCloud; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Available tools

ToolWhat it does
ClineThe Cline tool exposed by this server.
TasksThe Tasks tool exposed by this server.
InformationThe Information tool exposed by this server.

How to install the MCP MCP server

{
  "mcpServers": {
    "luma": {
      "type": "streamable-http",
      "url": "https://luma.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

VariableDescriptionRequired
ACEDATACLOUD_API_TOKENCredential the server authenticates with.Yes
YOUR_API_TOKENCredential the server authenticates with.Yes
ACEDATACLOUD_API_BASE_URLEndpoint or connection string the server talks to.Yes
ACEDATACLOUD_OAUTH_CLIENT_IDConfiguration value read at startup.Optional
ACEDATACLOUD_PLATFORM_BASE_URLEndpoint or connection string the server talks to.Yes

Example prompts to try

  • Use MCP to Cline.
  • Use MCP to Tasks.
  • Use MCP to Information.

Frequently asked questions

It connects MCP to MCP-compatible AI assistants such as Claude and Cursor, exposing 3 tools (Cline, Tasks, Information) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP directly.