How to Use the Livestorm MCP in AutoGen

Let your AutoGen agents debate and coordinate Livestorm webinar schedules and registration workflows.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Livestorm MCP to AutoGen

Create your Vinkius account to connect Livestorm to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Livestorm with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Coordinate events via multi-agent debate

Your agents check `list_events` and `list_webinar_rooms` to ensure there are no timing or room conflicts before scheduling. Once verified, they run `create_event` to book the slot. This consensus-driven process prevents scheduling mistakes. The agents negotiate the best times and configurations in their group chat, executing the final setup only when all constraints are met.

Audit registrations with an AutoGen MCP Server setup

Your auditing agent pulls registration details using `list_registrations` to run automated quality checks. It reviews the email formats to flag spam domains before they are finalized. If the agents find issues, they discuss how to handle them. They can use `get_registration` to drill down into specific records, ensuring only clean lead data enters your sales pipeline.

Automate post-event reporting and replays

Your reporting agent calls `list_analytics` to compile attendance rates as soon as the webinar ends. Another agent then runs `send_replay` to distribute the recording. This eliminates manual coordination after a live broadcast. The agents check the attendee list via `list_attendees` first, ensuring the replay link only goes to verified participants.

Setup guide

Set up Livestorm 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 Livestorm 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="Livestorm_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Livestorm data")
print(result.messages[-1].content)

Get your connection token →

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="Livestorm_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Livestorm data")
    print(result.messages[-1].content)

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 Livestorm. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Livestorm now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Livestorm MCP in AutoGen

Use the AutoGen MCP extension to load the tools from your Vinkius URL. The adapter handles the schema conversion automatically, making the tools available to your AssistantAgent.

Yes. If your agents are configured to run tasks concurrently, they can make multiple calls like `list_events` and `list_webinar_rooms` at the same time to speed up coordination.

You can set rate limits on your agent's execution loops or use human-in-the-loop approval. This prevents agents from getting stuck in a debate loop that repeatedly calls `list_registrations`.

Yes. The Vinkius platform manages the server hosting, allowing your AutoGen agents to connect via secure HTTP transport using a single endpoint token.

Your API token is injected securely into the Vinkius vault and never exposed to the agents. Event details, room configurations, and attendee data are processed in memory and never written to persistent disk.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript