How to Use the ContentGroove MCP in CrewAI

Q: Can ContentGroove work with specialized CrewAI agents?

Yes, use the toolfilter option to limit which agent has access to specific tools. This ensures only your 'Editor' agent can trigger clip creation.

Q: How do I monitor ContentGroove status in CrewAI?

Create a monitoring agent that runs a scheduled task using getmediastatus. It can alert your main agent when a video finishes processing.

Deploy a CrewAI crew to research, clip, and manage video content automatically.

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Connect ContentGroove MCP to CrewAI

Create your Vinkius account to connect ContentGroove 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 ContentGroove with CrewAI

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CrewAI agents handling video ingest

Assign an agent the `create_direct_upload` tool to handle incoming video tasks. The agent gets the signed URL and passes it to the next agent in your crew. This setup allows for a hand-off between research and production. One agent prepares the upload, while another monitors the status using `get_media_status`.

Automated highlight editing in CrewAI

Use `list_all_clips` to let your analyst agent review what the system generated. It can filter for quality or relevance before deciding to publish. `get_clip_details` provides the granular data an agent needs to write summaries. Your crew works autonomously to organize your media library.

Multi-agent media project control with CrewAI

Give your moderator agent access to `list_media` for periodic auditing. It tracks every project and ensures that your video archives stay organized. If an agent identifies an old project, it can call `get_media_details` to confirm the status. This keeps your media operations running without you needing to check the dashboard manually.

Setup guide

Set up ContentGroove 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 ContentGroove tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent ContentGroove 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="ContentGroove Analyst",
        goal="Access and analyze ContentGroove data via MCP.",
        backstory="Expert analyst with direct ContentGroove access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent ContentGroove 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 ContentGroove. 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 ContentGroove MCP in CrewAI

Include the server in your agent's MCP configuration. Your crew can then share access to tools like `list_all_clips` across different roles.

Yes, use the tool_filter option to limit which agent has access to specific tools. This ensures only your 'Editor' agent can trigger clip creation.

Create a monitoring agent that runs a scheduled task using `get_media_status`. It can alert your main agent when a video finishes processing.

It does. You can assign the manager agent the ability to call `list_media` to coordinate the workload across the rest of the crew.

Your video library is shielded by unique endpoint tokens assigned to your session. We enforce strict boundary controls, so agents only interact with the media files you explicitly authorize.

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