wheattoast11 mcp video gen
by wheattoast11
Luma AI Video + Audio + Image Generation and RunwayML Video Generation from Image and Text
What is wheattoast11 mcp video gen
RunwayML + Luma AI MCP Server
This MCP server provides tools to interact with the RunwayML and Luma AI APIs for video and image generation tasks.
Features
- Generate videos from text prompts (RunwayML or Luma AI).
- Generate videos from images (RunwayML or Luma AI).
- Generate images from text prompts (Luma AI).
- Manage Luma AI generations (list, get, delete).
- Add audio to Luma AI generations.
- Upscale Luma AI generations.
- Enhance prompts using OpenRouter LLMs before generation.
Prerequisites
- Node.js (v18 LTS or later recommended)
- npm (usually included with Node.js)
- API Keys:
- RunwayML API Secret
- Luma AI API Key
- OpenRouter API Key (for the
enhance_prompt
tool)
Installation
- Clone or Download: Obtain the server code.
- Navigate to Directory: Open a terminal in the server's root directory (
runwayml-mcp-server
). - Install Dependencies:
npm install
Configuration
- Create
.env
file: In the server's root directory, create a file named.env
. - Add API Keys: Add your API keys to the
.env
file:
Replace the placeholder values with your actual keys.RUNWAYML_API_SECRET=your_runwayml_api_secret_here LUMAAI_API_KEY=your_luma_api_key_here OPENROUTER_API_KEY=your_openrouter_api_key_here
Running the Server
- Build the Server: Compile the TypeScript code:
npm run build
- Start the Server:
You should see a message likenpm start
RunwayML MCP server running on stdio
in your terminal's error output (stderr).
MCP Client Setup (e.g., Claude Desktop App, Cline)
Configure your MCP client to connect to this server. The exact steps depend on the client, but you'll typically need to provide:
- Name: A descriptive name (e.g.,
runway-luma-server
) - Command:
node
- Arguments: The full path to the compiled server index file (e.g.,
/path/to/your/runwayml-mcp-server/build/server-index.js
) - Environment Variables:
RUNWAYML_API_SECRET
: Your RunwayML API SecretLUMAAI_API_KEY
: Your Luma AI API KeyOPENROUTER_API_KEY
: Your OpenRouter API Key
Example Configuration (Conceptual):
{
"mcpServers": {
"runway-luma-server": {
"command": "node",
"args": ["`/full/path/to/runwayml-mcp-server/build/server-index.js"],`
"env": {
"RUNWAYML_API_SECRET": "your_runwayml_api_secret_here",
"LUMAAI_API_KEY": "your_luma_api_key_here",
"OPENROUTER_API_KEY": "your_openrouter_api_key_here"
},
"disabled": false,
"autoApprove": []
}
}
}
(Remember to replace /full/path/to/
with the actual path on your system)
Available Tools
generate_text_to_video
: Generates video from text.provider
: (Optional)runwayml
(default) orlumaai
.promptText
: (Required) The text prompt.runway_model
: (Optional) Runway model (e.g., "gen-2").runway_resolution
: (Optional) Runway resolution (1280:768
or768:1280
).runway_watermark
: (Optional) Boolean, defaultfalse
.luma_model
: (Optional) Luma model (ray-flash-2
,ray-2
(default),ray-1-6
).luma_aspect_ratio
: (Optional) Luma aspect ratio (e.g.,16:9
(default),1:1
).luma_loop
: (Optional) Boolean.duration
: (Optional) Video duration in seconds (number).seed
: (Optional) Generation seed (number).
generate_image_to_video
: Generates video from an image.provider
: (Optional)runwayml
(default) orlumaai
.promptImage
: (Required) URL of the input image, or for Runway, an array[{uri: "url", position: "first" | "last"}]
.promptText
: (Optional) Text prompt to accompany the image.runway_model
: (Optional) Runway model (gen3a_turbo
(default)).runway_duration
: (Optional) Runway duration (5
(default) or10
).runway_ratio
: (Optional) Runway resolution (1280:768
or768:1280
).runway_watermark
: (Optional) Boolean, defaultfalse
.luma_model
: (Optional) Luma model (ray-flash-2
,ray-2
(default),ray-1-6
).luma_aspect_ratio
: (Optional) Luma aspect ratio (e.g.,16:9
(default)).luma_loop
: (Optional) Boolean.seed
: (Optional) Generation seed (number).
enhance_prompt
: Refines a prompt using OpenRouter.original_prompt
: (Required) The prompt to enhance.model
: (Optional) OpenRouter model name (defaults to a capable model likeanthropic/claude-3.5-sonnet
).instructions
: (Optional) Specific instructions for the enhancement.
luma_generate_image
: Generates an image using Luma AI.prompt
: (Required) Text prompt.aspect_ratio
: (Optional) Luma aspect ratio (16:9
(default)).model
: (Optional) Luma image model (photon-1
(default),photon-flash-1
).image_ref
: (Optional) Array of image reference objects ({url: string, weight?: number}
). Max 4.style_ref
: (Optional) Array of style reference objects ({url: string, weight?: number}
). Max 1.character_ref
: (Optional) Character reference object ({ identity0: { images: [url1, ...] } }
).modify_image_ref
: (Optional) Modify image reference object ({url: string, weight?: number}
).
luma_list_generations
: Lists previous Luma AI generations.limit
: (Optional) Number of results (default 10).offset
: (Optional) Offset for pagination (default 0).
luma_get_generation
: Gets details for a specific Luma AI generation.generation_id
: (Required) UUID of the generation.
luma_delete_generation
: Deletes a specific Luma AI generation.generation_id
: (Required) UUID of the generation.
luma_get_camera_motions
: Lists supported camera motions for Luma AI prompts. (No parameters).luma_add_audio
: Adds audio to a Luma generation.generation_id
: (Required) UUID of the generation.prompt
: (Required) Prompt for the audio.negative_prompt
: (Optional) Negative prompt for audio.
luma_upscale
: Upscales a Luma generation.generation_id
: (Required) UUID of the generation.resolution
: (Optional) Target resolution (1080p
(default) or4k
).
(Note: For tools involving generation (generate_*
, luma_upscale
), the server initiates the task and returns immediately. Progress updates and the final result URL will be sent via MCP progress notifications.)
Example Workflows
Here are examples of how to combine the server's tools for common use cases:
1. Music Video Snippet (Cyberpunk Noir)
Goal: Create a 5-second cyberpunk noir video clip for the lyric "Neon rivers flowing through a city of chrome".
Steps:
-
Generate Base Image (Luma):
{ "tool_name": "luma_generate_image", "arguments": { "prompt": "Overhead shot of a dark, rainy cyberpunk city street at night. Bright neon signs reflect on wet pavement, resembling rivers of light flowing between towering chrome skyscrapers. Film noir aesthetic, photorealistic.", "aspect_ratio": "16:9" } }
(Wait for image generation to complete and get the image URL)
-
Animate Image (Luma):
{ "tool_name": "generate_image_to_video", "arguments": { "provider": "lumaai", "promptImage": "{IMAGE_URL_FROM_STEP_1}", "promptText": "Slow pan left across the rainy cyberpunk cityscape, neon lights flickering subtly.", "luma_aspect_ratio": "16:9", "duration": 5 } }
(Wait for video generation to complete)
2. Product Ad Concept (Floating Earbud)
Goal: Create a 5-second video showing a futuristic earbud floating in a minimalist environment.
Steps:
-
Generate Scene with Product Reference (Luma):
{ "tool_name": "luma_generate_image", "arguments": { "prompt": "A single, sleek futuristic wireless earbud floats weightlessly in the center of a bright, minimalist white room with soft, diffused ambient light. Zero gravity effect.", "aspect_ratio": "1:1", "image_ref": [{ "url": "{PRODUCT_IMAGE_URL}", "weight": 0.8 }] } }
(Wait for image generation to complete and get the image URL)
-
Animate Scene (Luma):
{ "tool_name": "generate_image_to_video", "arguments": { "provider": "lumaai", "promptImage": "{IMAGE_URL_FROM_STEP_1}", "promptText": "The earbud slowly rotates and drifts gently in zero gravity.", "luma_aspect_ratio": "1:1", "duration": 5 } }
(Wait for video generation to complete)
3. Image Animation (RunwayML Gen3a)
Goal: Animate an existing image using RunwayML's Gen3a model.
Steps:
- (Optional) Generate Base Image (Luma): Use
luma_generate_image
if you don't have an image. - Animate Image (RunwayML):
(Wait for video generation to complete){ "tool_name": "generate_image_to_video", "arguments": { "provider": "runwayml", "promptImage": "{YOUR_IMAGE_URL}", "promptText": "Subtle zoom in, cinematic lighting.", "runway_model": "gen3a_turbo", "runway_duration": "5", "runway_ratio": "1280:768" // Or "768:1280" } }
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Frequently Asked Questions
What is MCP?
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.
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MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.
How do MCP Servers work?
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Are MCP Servers secure?
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