How do I check if my video generation is finished?

Use the `lm.get_generation` tool with the Generation ID provided. Your agent will poll the Luma API and report the current state (queued, dreaming, or completed). Once finished, it will return the final MP4 video URL.

Can I control the camera movement in my AI-generated video?

Absolutely. Use the `lm.camera_control` tool. You can provide a scene prompt and a JSON block defining the movement type (e.g., orbit, pan, tilt) and magnitude, allowing for professional cinematographic directing.

Can my agent extend an existing Luma video with more footage?

Yes. The `lm.extend_video` tool allows you to provide a continuation prompt and a previous Generation ID. Your agent will trigger Luma to seamlessly expand the scene, maintaining visual and structural consistency.

Luma AI (Generative Video & Creative) MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Luma AI (Generative Video & Creative)
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Luma AI (Generative Video & Creative) through Vinkius, pass the Edge URL in the `mcps` parameter and every Luma AI (Generative Video & Creative) tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Luma AI (Generative Video & Creative) Specialist",
    goal="Help users interact with Luma AI (Generative Video & Creative) effectively",
    backstory=(
        "You are an expert at leveraging Luma AI (Generative Video & Creative) tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Luma AI (Generative Video & Creative) "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Luma AI (Generative Video & Creative) MCP Server

Connect your Luma AI account to any AI agent and take full control of state-of-the-art generative video production and professional creative tools through natural conversation.

When paired with CrewAI, Luma AI (Generative Video & Creative) becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Luma AI (Generative Video & Creative) tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Cinematic Text-to-Video — Generate high-fidelity AI videos from scenic descriptions using Luma Dream Machine (Ray-2 model) directly from your agent
Image Animation — Transform static frames into dynamic videos (image-to-video) with industry-leading motion coherence and photorealism
Professional Camera Control — Direct your AI shots with specific movements including pan, tilt, dolly, and orbit using structured movement parameters
Video Extension & Looping — Seamlessly continue existing scenes with additional footage or create perfect looping videos for social media and backgrounds
Keyframe Interpolation — Create smooth, high-quality video transitions between two distinct keyframe images to bridge visual concepts effectively
Photorealistic Text-to-Image — Generate stunning high-resolution images using the Luma Photon-1 model for rapid visual iteration and design
Task Orchestration — Manage asynchronous generation jobs, poll for status updates (queued, dreaming, completed), and monitor your API credit balance securely

The Luma AI (Generative Video & Creative) MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Luma AI (Generative Video & Creative) to CrewAI via MCP

Follow these steps to integrate the Luma AI (Generative Video & Creative) MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Luma AI (Generative Video & Creative)

Why Use CrewAI with the Luma AI (Generative Video & Creative) MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Luma AI (Generative Video & Creative) through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Luma AI (Generative Video & Creative) + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Luma AI (Generative Video & Creative) MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Luma AI (Generative Video & Creative) for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Luma AI (Generative Video & Creative), analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Luma AI (Generative Video & Creative) tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Luma AI (Generative Video & Creative) against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Luma AI (Generative Video & Creative) MCP Tools for CrewAI (10)

These 10 tools become available when you connect Luma AI (Generative Video & Creative) to CrewAI via MCP:

lm.camera_control

Generate video with specific camera movements using Luma Dream Machine. Supports pan, tilt, dolly, orbit

lm.delete_generation

Delete a Luma Dream Machine generation and its video

lm.extend_video

Extend an existing Luma video with additional footage. Seamlessly continues the scene

lm.get_credits

Get current Luma Dream Machine credit balance

lm.get_generation

Get the status and result of a Luma Dream Machine generation. Returns state (queued/dreaming/completed/failed) and video URL

lm.image_to_video

Animate a still image into video using Luma Dream Machine. Image becomes the first frame

lm.interpolate

Create smooth video transition between two keyframe images using Luma Dream Machine

lm.list_generations

List recent Luma Dream Machine generations. Returns generation IDs, prompts, states, and timestamps

lm.text_to_image

Generate photorealistic images using Luma Photon-1 model

lm.text_to_video

), and loop (true/false). Poll get_generation for results. Generate cinematic AI video from a text prompt using Luma Dream Machine (Ray-2 model). Industry-leading motion coherence and photorealism

Example Prompts for Luma AI (Generative Video & Creative) in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Luma AI (Generative Video & Creative) immediately.

"Generate a 5-second cinematic video of a futuristic spaceship landing on a neon planet"

"Animate this static image into a video: [url]"

"Show me my last 3 Luma generations"

Troubleshooting Luma AI (Generative Video & Creative) MCP Server with CrewAI

Common issues when connecting Luma AI (Generative Video & Creative) to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Luma AI (Generative Video & Creative) + CrewAI FAQ

Common questions about integrating Luma AI (Generative Video & Creative) MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.