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

Q: How do specialized agents in CrewAI use the Luma AI (Generative Video & Creative) MCP Server?

You assign tools like lm.cameracontrol to your Director agent and lm.texttovideo to your Producer agent. CrewAI manages the collaboration, letting agents pass generation IDs and video files between each other.

Q: How do I limit which Luma AI (Generative Video & Creative) tools a CrewAI agent can access?

Use the toolfilter option with MCPServerHTTP to expose only specific tools, like lm.getcredits for an auditor agent or lm.texttovideo for a generator agent.

Q: How does the crew handle failed video generations?

If lm.getgeneration returns a failed state, the supervisor agent analyzes the failure, updates the prompt, and tasks the creator agent with generating a new version.

Q: How does this MCP Server protect my video prompt data when running CrewAI agents?

All API requests, including prompts sent to lm.texttovideo and video URLs returned by lm.getgeneration, are processed inside secure, isolated V8 sandboxes. Your data is never cached, stored, or exposed to external networks.

Coordinate a team of AI agents to write scripts, direct cameras, and generate cinematic videos using CrewAI and Luma AI.

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

Create your Vinkius account to connect Luma AI (Generative Video & Creative) to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Luma AI (Generative Video & Creative) with CrewAI

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Multi-Agent Cinematic Direction in CrewAI

`lm.camera_control` allows a specialized Director agent in your crew to dictate specific camera paths like pan, tilt, or dolly. Meanwhile, a Screenwriter agent drafts the scene prompts and passes them to the Director. This MCP Server exposes the tool directly to the Director agent, who combines the script with camera vectors to execute `lm.text_to_video`. CrewAI's hierarchical execution ensures the writer and director agents coordinate their outputs without friction.

Sequential Scene Generation and Extension

`lm.extend_video` is used by your editor agent to maintain visual continuity across longer sequences. Once the first agent generates a 4-second clip, the editor agent takes the video ID and calls the extension tool to continue the action. The crew monitors the progress by calling `lm.get_generation` at regular intervals. If temporal drift occurs, a supervisor agent can reject the clip and instruct the generator agent to rebuild the scene with a modified prompt.

Autonomous Video Pipeline Auditing via MCP Server

`lm.get_credits` enables an auditor agent to track the crew's resource consumption. Before launching a multi-clip generation task, the auditor checks the remaining balance to ensure the crew has enough funds. If the balance is insufficient, the auditor agent escalates the issue by pausing the crew's execution. The crew also uses `lm.list_generations` to keep track of all active and completed assets in the workspace.

Setup guide

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

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Luma AI (Generative Video & Creative) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Luma AI (Generative Video & Creative) Analyst",
    goal="Access and analyze Luma AI (Generative Video & Creative) data via MCP.",
    backstory="Expert analyst with direct Luma AI (Generative Video & Creative) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Luma AI (Generative Video & Creative) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Luma AI (Generative Video & Creative) Analyst",
        goal="Access and analyze Luma AI (Generative Video & Creative) data via MCP.",
        backstory="Expert analyst with direct Luma AI (Generative Video & Creative) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Luma AI (Generative Video & Creative) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

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 CrewAI

You assign tools like `lm.camera_control` to your Director agent and `lm.text_to_video` to your Producer agent. CrewAI manages the collaboration, letting agents pass generation IDs and video files between each other.

Yes. An editor agent can take the output from a previous task and call `lm.extend_video` to add new frames, ensuring the visual style remains consistent across the sequence.

Use the `tool_filter` option with `MCPServerHTTP` to expose only specific tools, like `lm.get_credits` for an auditor agent or `lm.text_to_video` for a generator agent.

If `lm.get_generation` returns a failed state, the supervisor agent analyzes the failure, updates the prompt, and tasks the creator agent with generating a new version.

All API requests, including prompts sent to `lm.text_to_video` and video URLs returned by `lm.get_generation`, are processed inside secure, isolated V8 sandboxes. Your data is never cached, stored, or exposed to external networks.

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