How to Use the Kling AI (Generative Video & Image) MCP in CrewAI

Q: Can one agent in CrewAI start a video job with Kling AI (Generative Video & Image) and another agent check the status?

Yes. The task ID returned by texttovideo is just a string. The first agent can save this ID to the crew's shared memory, and a second agent can then use it as an argument for the getvideotask tool.

Q: How do I limit which CrewAI agents can use expensive tools like texttovideo?

When defining your Agent in CrewAI, you can use the toolfilter argument within the MCPServerHTTP configuration. This lets you explicitly list which tools from this MCP server that specific agent is allowed to access, giving you fine-grained control.

Q: Are the prompts and images I send to the server private?

Yes. When your agent uses texttoimage, the text prompt and any source images are handled within a dedicated, sandboxed session on Vinkius. The data is encrypted during transfer and is automatically wiped after the getimagetask polling is complete. It's not used for any other purpose.

Equip your CrewAI agents with video and image generation tools. Assign roles for an autonomous content creation pipeline.

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Connect Kling AI (Generative Video & Image) MCP to CrewAI

Create your Vinkius account to connect Kling AI (Generative Video & Image) 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 Kling AI (Generative Video & Image) with CrewAI

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Build an Autonomous Video Factory

Assign the `text_to_video` tool to a "Director Agent." A separate "Producer Agent" can be tasked with polling the `get_video_task` status. This division of labor is what CrewAI is all about. Once the Producer Agent confirms a video is ready, it can pass the final MP4 URL to a "Social Media Agent" for posting. The entire process runs without any human intervention, from prompt to publication.

Specialized Agents for Visual Effects

Create a "VFX Artist Agent" and give it access to `image_to_video` and `lip_sync_video`. Another agent, the "Casting Director," could use `text_to_image` to generate character concepts. The agents collaborate. The Casting Director generates an image and passes it to the VFX Artist, which then animates it and adds dialogue. This MCP server provides the specific tools each specialized agent needs to do its job.

Your CrewAI MCP Server for Media Ops

This isn't just one tool; it's a toolkit for a team. A "Quality Assurance Agent" could be responsible for `list_video_tasks`, checking for failed jobs and re-assigning them. An "Archivist Agent" could take successful video URLs and log them. You can configure CrewAI to expose only certain tools to certain agents. Give the `virtual_try_on` tool to your "E-commerce Agent" but not your "Content Writing Agent." It's about building a structured, autonomous organization with this MCP connection.

Setup guide

Set up Kling AI (Generative Video & Image) 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 Kling AI (Generative Video & Image) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Kling AI (Generative Video & Image) 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="Kling AI (Generative Video & Image) Analyst",
        goal="Access and analyze Kling AI (Generative Video & Image) data via MCP.",
        backstory="Expert analyst with direct Kling AI (Generative Video & Image) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Kling AI (Generative Video & Image) 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 Kling 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 Kling AI (Generative Video & Image) MCP in CrewAI

Create a "Writer Agent" to generate prompts, a "Video Agent" with the `text_to_video` and `get_video_task` tools, and a "Publisher Agent." The Writer passes a prompt, the Video Agent creates and retrieves the video, and the Publisher posts it.

Yes. The task ID returned by `text_to_video` is just a string. The first agent can save this ID to the crew's shared memory, and a second agent can then use it as an argument for the `get_video_task` tool.

Assign a dedicated "QA Agent." Its role is to periodically use `list_video_tasks` to find tasks with a 'failed' status. It can then delegate the task of retrying the job, perhaps with a modified prompt, back to the appropriate creation agent.

When defining your Agent in CrewAI, you can use the `tool_filter` argument within the `MCPServerHTTP` configuration. This lets you explicitly list which tools from this MCP server that specific agent is allowed to access, giving you fine-grained control.

Yes. When your agent uses `text_to_image`, the text prompt and any source images are handled within a dedicated, sandboxed session on Vinkius. The data is encrypted during transfer and is automatically wiped after the `get_image_task` polling is complete. It's not used for any other purpose.

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