How to Use the Luma AI (Generative Video & Creative) MCP in Claude Code

Q: How do I add the Luma AI (Generative Video & Creative) MCP Server to Claude Code?

Run the command claude mcp add --transport http luma-ai-generative-video-creative-mcp -- in your terminal. This registers the server in your local /.claude.json configuration file.

Q: Can I pipe the output of my generations to other terminal utilities?

Yes, you can command the agent to output the results of lm.listgenerations or lm.getgeneration as raw JSON. This allows you to pipe the video URLs or metadata to other command-line tools like curl or jq.

Run headless Luma Dream Machine pipelines directly from your terminal using Claude Code and this managed MCP Server.

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Connect Luma AI (Generative Video & Creative) MCP to Claude Code

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Setup Luma AI (Generative Video & Creative) with Claude Code

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Scriptable Video Generation via the Claude Code CLI

The `lm.text_to_video` tool brings programmatic video generation straight to your terminal using this MCP server. You can pipe prompt lists directly into Claude Code to kick off batch renders. This removes the need for manual browser clicks and fits perfectly into script-driven workflows. Because it runs in the shell, you can chain commands easily. Your agent checks your remaining API balance with `lm.get_credits`, triggers the render, and outputs the progress. It polls `lm.get_generation` and returns the final video URL directly to stdout.

Command-Line Camera Control and Video Extension

The `lm.camera_control` tool lets you script complex camera movements using pan, tilt, zoom, and orbit vectors via the MCP interface. Claude Code parses your terminal arguments and maps them to the API parameters. You get precise, command-line control over your visual composition. For iterative work, the agent can call `lm.extend_video` to append new frames to an existing clip or use `lm.image_to_video` on local file paths. If a render fails to meet your criteria, you can instantly run `lm.delete_generation` to keep your workspace clean.

Automate Keyframe Transitions and Image Generation

The `lm.interpolate` tool generates smooth transitions between two static keyframes. Claude Code uses this to bridge visual gaps in your automated rendering pipelines. It takes local image paths, uploads them, and returns a fluid transition video. To generate those source assets on the fly, the agent calls `lm.text_to_image` using the Photon-1 model. This lets you build a completely headless pipeline that goes from text prompt to static image, and then to a fully animated video sequence.

Setup guide

Set up Luma AI (Generative Video & Creative) MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see luma-ai-generative-video-creative-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest Luma AI (Generative Video & Creative) transactions." It will automatically discover and invoke the available Luma AI (Generative Video & Creative) tools.

Terminal

claude mcp add --transport http luma-ai-generative-video-creative-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

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Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the Luma AI (Generative Video & Creative) MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "luma-ai-generative-video-creative-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Luma AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Luma AI (Generative Video & Creative) MCP in Claude Code

Run the command `claude mcp add --transport http luma-ai-generative-video-creative-mcp -- ` in your terminal. This registers the server in your local `~/.claude.json` configuration file.

Yes, you can execute video generation scripts in GitHub Actions or Docker containers. Claude Code interacts with the server via the command line, making it easy to automate automated asset generation.

Simply ask the agent to check your remaining balance in the terminal. It runs `lm.get_credits` and prints your current credit count directly to your shell output.

Yes, you can command the agent to output the results of `lm.list_generations` or `lm.get_generation` as raw JSON. This allows you to pipe the video URLs or metadata to other command-line tools like curl or jq.

Your credit checks and usage logs are protected by Vinkius's zero-trust V8 isolate architecture. No sensitive API credentials or credit balances are exposed to the local shell environment, keeping your account details completely isolated.

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