How to Use the Loom (Async Video Messaging) MCP in CrewAI

Q: Can CrewAI agents collaborate on Loom (Async Video Messaging) tasks?

Yes. You can have one agent gather data with listvideos while another agent processes it. They share memory to ensure the workflow stays consistent.

Q: How do I limit tool access for Loom (Async Video Messaging) in CrewAI?

Use the toolfilter in your agent configuration. This ensures that only the necessary tools, like gettranscript, are available to specific members of your crew.

Q: How do I update video metadata with CrewAI?

Give your agent the updatevideo tool. You can then instruct the agent to rename videos based on specific naming conventions or project codes.

Deploy specialized agents with CrewAI to automate your Loom (Async Video Messaging) operations.

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Connect Loom (Async Video Messaging) MCP to CrewAI

Create your Vinkius account to connect Loom (Async Video Messaging) 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 Loom (Async Video Messaging) with CrewAI

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Specialized agent roles for video analysis

Assign a 'Researcher' agent to call `get_transcript` and `get_video` to summarize team updates. It processes long-form content so the rest of your crew doesn't have to. This keeps information flowing through your team. Your agents handle the heavy lifting of parsing internal communication.

Autonomous workspace maintenance with the MCP Server

Set up a 'Moderator' agent to watch your library using `list_videos`. If it finds outdated material, it executes `delete_video` to reclaim space. This creates a self-cleaning workspace. You define the rules, and your crew handles the maintenance autonomously.

Engagement tracking across your CrewAI team

Have your 'Analyst' agent pull `get_video_analytics` to report on which videos get the most attention. It compiles a summary for your daily stand-up. You stay informed without watching every clip. The data is converted into actionable insights by your specialized agents.

Setup guide

Set up Loom (Async Video Messaging) 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 Loom (Async Video Messaging) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Loom (Async Video Messaging) 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 Loom. 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 Loom (Async Video Messaging) MCP in CrewAI

Yes. You can have one agent gather data with `list_videos` while another agent processes it. They share memory to ensure the workflow stays consistent.

Use the `tool_filter` in your agent configuration. This ensures that only the necessary tools, like `get_transcript`, are available to specific members of your crew.

It does. You can have multiple agents querying the server at once, provided your account limits allow it. It makes your crew much faster.

Give your agent the `update_video` tool. You can then instruct the agent to rename videos based on specific naming conventions or project codes.

Vinkius uses a zero-trust sandbox. The server only interacts with the specific video metadata you authorize, ensuring your account credentials remain private.

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