How to Use the Accelevents MCP in AutoGen

Q: Can I create an AutoGen agent that only reports on Accelevents data and can't change anything?

Absolutely. The tools provided by this MCP server—listevents, listattendees, listexhibitors, and listsessions—are all read-only. Your agents can only fetch data, not modify it.

Q: How does AutoGen handle the outputs from the Accelevents MCP server tools?

The McpToolAdapter automatically converts the JSON output from the tools into a format the agents can read and discuss. This output becomes part of their conversational history, which they use to make their next move.

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Setup Accelevents with AutoGen

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Set Up Agent Teams for Event Ops

AutoGen lets you build a team of specialized agents that talk to each other to solve problems. You could have a "RegistrationAgent" that uses the `list_attendees` tool to monitor sign-ups. It then reports its findings to a "MarketingAgent". The MarketingAgent, in turn, might decide to trigger a new campaign based on the registration numbers. They work together, using the Accelevents data from this MCP server as the source of truth for their conversation.

Debate and Verify Event Data

This isn't about one agent blindly executing tasks. It's about consensus. One agent can draft a summary of upcoming sessions using `list_sessions`. You can then have a second "ReviewerAgent" that double-checks the facts by calling the same tool itself. The agents can debate any discrepancies they find before presenting a final, verified answer. It's a system of checks and balances for managing your event information.

Your AutoGen MCP Server for Event Management

This MCP server provides the specific tools your AutoGen agents need to interact with Accelevents. The `mcp_server_tools` function makes it simple to give your agents the ability to `list_events`, `list_exhibitors`, and more. Because AutoGen is built on conversation, the agents can discuss which tool is right for the job. One agent might suggest checking exhibitors while another argues that checking session schedules is the higher priority.

Setup guide

Set up Accelevents 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 Accelevents 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="Accelevents_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Accelevents 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="Accelevents_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Accelevents 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 Accelevents. 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 Accelevents MCP in AutoGen

Each agent in an AutoGen group can be given access to the Accelevents toolset. They coordinate through conversation, deciding who should call which tool and when, based on the roles you've assigned them.

Absolutely. The tools provided by this MCP server—`list_events`, `list_attendees`, `list_exhibitors`, and `list_sessions`—are all read-only. Your agents can only fetch data, not modify it.

You could set up a "Planning" agent that pulls exhibitor and session data, and a "Finance" agent that pulls attendee and ticket data. They could then collaborate to produce a forecast report for an upcoming event, all within an AutoGen chat.

The `McpToolAdapter` automatically converts the JSON output from the tools into a format the agents can read and discuss. This output becomes part of their conversational history, which they use to make their next move.

The agents you build will have access to the data returned by the tools: event lists, attendee names and ticket types, exhibitor details, and session schedules. Vinkius secures the connection to the MCP server, so your API keys are never shared directly with the agent framework.

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