How to Use the Vimeo MCP in CrewAI

Q: How can I check my profile details using Vimeo and CrewAI?

The crew uses getme to pull your authenticated user information. The 'Researcher Agent' gathers this data, passing it to the 'Analyzer Agent' for immediate review.

Q: Can I find public videos using Vimeo and CrewAI?

Sure thing. You assign a specific agent task: searchvideos. This allows you to build dedicated pipelines that only focus on finding external, public content across Vimeo.

Q: Does the MCP Server allow me to delete videos with CrewAI?

Yes, the team can perform deletions using deletevideo. Because this is a critical action, you'll want one agent dedicated solely to confirming human approval before executing the tool.

Q: Can I list groups and channels for Vimeo and CrewAI?

The 'Scout Agent' handles this. It sequentially calls both listgroups and listchannels, consolidating all results into a shared memory accessible to the rest of your team.

Build autonomous Vimeo operations with CrewAI's specialized agent teams.

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Connect Vimeo MCP to CrewAI

Create your Vinkius account to connect Vimeo 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 Vimeo with CrewAI

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Multi-Agent Video Auditing for MCP Server

You don't run one script; you deploy a team. Agent A can call `list_videos` to gather the list, while Agent B specializes in analyzing that data by calling `get_video`. This specialized collaboration makes the audit thorough. A third agent can then take action, maybe using `delete_video`, based on the findings of the first two agents.

Autonomous Content Discovery via CrewAI

Need to find all assets? The crew works together. One agent runs `list_showcases` to identify albums, and another agent then iterates through those results calling `list_folders` for deeper context. This autonomous process means the operation continues until all relevant Vimeo data has been mapped out.

Managing User Assets with CrewAI

The team can monitor and act. For example, a 'Moderator Agent' watches for user input via `get_me` status checks. If the status changes, another agent might run `update_video` to correct metadata automatically. The shared memory between agents ensures that every piece of data gathered is available for subsequent actions.

Setup guide

Set up Vimeo 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 Vimeo tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

The crew uses `get_me` to pull your authenticated user information. The 'Researcher Agent' gathers this data, passing it to the 'Analyzer Agent' for immediate review.

Sure thing. You assign a specific agent task: `search_videos`. This allows you to build dedicated pipelines that only focus on finding external, public content across Vimeo.

Yes, the team can perform deletions using `delete_video`. Because this is a critical action, you'll want one agent dedicated solely to confirming human approval before executing the tool.

The 'Scout Agent' handles this. It sequentially calls both `list_groups` and `list_channels`, consolidating all results into a shared memory accessible to the rest of your team.

The server touches comprehensive video metadata, including asset ownership and modification history. This is exposed through tools like `get_video` for detailed analysis by the crew.

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