Luma AI

v1.0.0APIsstable

Powered by Ray (video) and Photon (image) models by Luma AI

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What is Luma AI?

Luma AI is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to powered by ray (video) and photon (image) models by luma ai

Powered by Ray (video) and Photon (image) models by Luma AI

This server falls under the APIs and Cloud Services categories on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • Powered by Ray (video) and Photon (image) models by Luma AI

Use Cases

Generate AI images and videos using Luma's Ray and Photon models.
Access cutting-edge generative AI capabilities for creative workflows.
lumalabs

Maintainer

LicenseMIT
Languagepython
Versionv1.0.0
UpdatedMay 5, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx luma-api

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Luma AI

Luma AI MCP Server connects AI assistants directly to Luma AI's generation APIs, enabling image creation via the Photon model and video creation via the Ray model through natural language prompts. Users can specify aspect ratios, quality settings, reference images, character references, and keyframe control for videos — all from within their MCP client conversation. It is designed for creative professionals and developers who want to integrate state-of-the-art generative media into AI-driven workflows without leaving their chat interface.

Prerequisites

  • Python 3.10 or later installed
  • A Luma AI account with an active API key (obtain from https://lumalabs.ai/api/keys)
  • An MCP client such as Claude Desktop
  • The Luma API MCP repository cloned locally (uses a setup.sh script for configuration)
1

Clone the repository

Clone the luma-api-mcp repository to your local machine. The setup is handled by a shell script rather than a package manager.

git clone https://github.com/lumalabs/luma-api-mcp.git
cd luma-api-mcp
2

Obtain your Luma AI API key

Visit https://lumalabs.ai/api/keys, sign in to your Luma AI account, and generate an API key. Copy the key — you will provide it during setup.

3

Run the setup script

Execute the setup script which installs dependencies and prompts you for your API key. The script configures the server so it can authenticate with Luma AI.

sh setup.sh
4

Configure your MCP client

Add the Luma AI MCP server to your client configuration. Pass your Luma API key as the LUMAAI_API_KEY environment variable so the server can authenticate with Luma's services.

{
  "mcpServers": {
    "luma-api": {
      "command": "python",
      "args": ["server.py"],
      "cwd": "/path/to/luma-api-mcp",
      "env": {
        "LUMAAI_API_KEY": "your-luma-api-key"
      }
    }
  }
}
5

Understand the two generation tools

The server exposes two main tools. create_image generates images using the Photon (photon-1) or Photon Flash (photon-flash-1) models with parameters for aspect ratio, style references, and up to 8 image reference inputs with weights. create_video generates videos using Ray 2 (ray-2), Ray Flash 2 (ray-flash-2), or Ray 1.6 (ray-1-6) with configurable aspect ratio, resolution (540p to 4K), duration (5s or 9s), looping, and keyframe control.

Luma AI Examples

Client configuration

Claude Desktop configuration to launch the Luma AI MCP server with API key authentication.

{
  "mcpServers": {
    "luma-api": {
      "command": "python",
      "args": ["server.py"],
      "cwd": "/path/to/luma-api-mcp",
      "env": {
        "LUMAAI_API_KEY": "your-luma-api-key"
      }
    }
  }
}

Prompts to try

Use these prompts with Claude to generate images and videos through Luma AI.

- "Generate a photorealistic image of a mountain lake at golden hour in 16:9 aspect ratio"
- "Create an image using photon-flash-1 of a futuristic cityscape at night"
- "Make a 5-second looping video of ocean waves using ray-2 in 4K resolution"
- "Generate a video starting with a sunrise and ending with a sunset, 9 seconds long"
- "Create an image of a dragon with a style reference from this image URL"

Troubleshooting Luma AI

API key rejected or 401 authentication error

Verify that LUMAAI_API_KEY is set to a valid active API key from https://lumalabs.ai/api/keys. The key must be from an account with API access enabled — free accounts may not have API access by default.

Image generation times out

Image generation via Photon typically takes 5-15 seconds. If your MCP client has a short timeout, increase it. Video generation with Ray takes 15-60 seconds depending on duration and resolution — do not cancel prematurely.

Video keyframe parameters are not applied

Keyframes must be specified as image URLs or generation IDs from prior Luma generations. Ensure the referenced image URLs are publicly accessible and that generation IDs correspond to completed (not pending) generations.

Frequently Asked Questions about Luma AI

What is Luma AI?

Luma AI is a Model Context Protocol (MCP) server that powered by ray (video) and photon (image) models by luma ai It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Luma AI?

Follow the installation instructions on the Luma AI GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with Luma AI?

Luma AI works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Luma AI free to use?

Yes, Luma AI is open source and available under the MIT license. You can use it freely in both personal and commercial projects.

Browse More APIs MCP Servers

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Quick Config Preview

{ "mcpServers": { "luma-api": { "command": "npx", "args": ["-y", "luma-api"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

Ready to use Luma AI?

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