How to Use the Bevy Community MCP in AutoGen

Debate community strategy with AutoGen and Bevy Community tools.

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Connect Bevy Community MCP to AutoGen

Create your Vinkius account to connect Bevy Community 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.

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Setup Bevy Community with AutoGen

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Claude

Perplexity

Debate Bevy Community data in AutoGen

Your agents use `get_event` and `list_event_types` to gather facts for their discussions. They challenge each other on these findings before reaching a consensus. This removes bias from your decision process. One agent analyzes the raw event data while another critiques the findings to ensure accuracy.

Multi-agent chapter coordination

Assign one agent to `list_user_chapters` and another to suggest engagement strategies. They negotiate based on the user's specific community memberships. The system converges on a plan that makes sense for the user. You get a deliberated result instead of a single, unverified suggestion.

Security and performance agents

Set a security agent to monitor `list_event_attendees` for privacy while a performance agent pushes for faster data delivery. They balance these competing needs. This prevents your agent from acting on incomplete information. It only proceeds once both agents agree that the data meets their respective criteria.

Setup guide

Set up Bevy Community 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 Bevy Community 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="Bevy Community_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

You pass the tool list into your assistant agent constructor. The adapter handles the conversion, letting your agents start their conversation immediately.

Your agents can invoke any of the tools to gather data. They then use that data to inform their arguments and debate.

It is built for that. Your agents use the tools to pull data and then reconcile their findings to reach a final decision.

Data flows through the conversation loop between your agents. It is not logged or stored by us beyond the ephemeral session duration.

Your session uses an authenticated token that expires. We enforce strict isolation so your agent conversations remain private to your local system.

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