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

Q: Can AutoGen agents coordinate to delete videos using Loom (Async Video Messaging)?

Yes, agents can discuss video metrics and call deletevideo once they agree a video is no longer needed. This consensus-driven approach protects your workspace from hasty deletions.

Q: How do AutoGen agents analyze video analytics with Loom (Async Video Messaging)?

Agents can call getvideoanalytics to retrieve detailed engagement logs. They can then debate whether completion rates are high enough to justify keeping a training video in the main folder.

Q: Can my agents list workspace members?

Yes, agents can use the listworkspacemembers tool to see who belongs to your workspace. This helps them assign video ownership or audit permissions during their discussions.

Deploy AutoGen agents to debate, audit, and manage your Loom (Async Video Messaging) workspace using this MCP Server.

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Setup Loom (Async Video Messaging) with AutoGen

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Multi-agent video audits with this MCP Server

AutoGen lets you set up specialized agents that collaborate to manage your video library. A compliance agent can call `get_transcript` to scan for sensitive information, while a manager agent decides whether to flag the video. By exposing this MCP Server to your agent group, they can discuss the transcript's contents and reach a consensus before taking action. No single agent makes a blind decision to alter your workspace.

Debate video retention and deletion policies

Let your agents debate which videos are safe to remove. One agent can pull low-engagement videos using `list_videos` and `get_video_analytics`, while another agent argues for keeping them based on folder context. Once they reach an agreement, they can execute `delete_video` to remove the stale asset. This prevents accidental loss of important historical team knowledge.

Collaborative workspace metadata updates in AutoGen

Your agents can work together to clean up poorly named videos. An editor agent drafts new titles based on metadata from `get_video`, while an approval agent checks them against company naming conventions. After the agents agree on the best title, they call `update_video` to apply the change. It ensures your workspace remains organized without requiring manual review of every single title.

Setup guide

Set up Loom (Async Video Messaging) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Loom (Async Video Messaging) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Loom (Async Video Messaging)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Loom (Async Video Messaging) data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Loom (Async Video Messaging)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Loom (Async Video Messaging) data")
    print(result.messages[-1].content)

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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 AutoGen

Use the McpToolAdapter to convert the MCP server tools for your AutoGen agents. You can then pass tools like `list_videos` directly to your AssistantAgent constructor.

Yes, agents can discuss video metrics and call `delete_video` once they agree a video is no longer needed. This consensus-driven approach protects your workspace from hasty deletions.

Agents can call `get_video_analytics` to retrieve detailed engagement logs. They can then debate whether completion rates are high enough to justify keeping a training video in the main folder.

Yes, agents can use the `list_workspace_members` tool to see who belongs to your workspace. This helps them assign video ownership or audit permissions during their discussions.

The integration runs inside a secure V8 sandbox, passing video metadata and transcripts directly to your local agents. Your API tokens and viewer analytics are never logged or exposed to third parties.

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