How to Use the Beekeeper MCP in AutoGen

Enable multi-agent debate in AutoGen with direct access to your Beekeeper workspace.

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Connect Beekeeper MCP to AutoGen

Create your Vinkius account to connect Beekeeper 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 Beekeeper with AutoGen

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Consensus-driven Beekeeper operations in AutoGen

Deploy multiple agents to debate the best way to handle a `send_message` request. One agent drafts the content, while another checks it against policy constraints. This prevents errors by forcing agents to negotiate before taking action in your Beekeeper streams. You get a deliberate, multi-perspective approach to every task.

Debate-based user management for AutoGen

Agents discuss which users to target when using `search_users` or `list_groups`. They challenge each other's assumptions to ensure the right people are reached. This is useful for sensitive communications where accuracy matters. The agents iterate until they reach a consensus on the correct recipient list.

Automated Beekeeper stream monitoring

Set up an agent to watch `list_posts` and trigger a discussion if specific keywords appear. The agents then decide whether to escalate the issue. This creates a responsive system that adapts to your team's activity. You don't just get alerts; you get agents that understand the context of the posts.

Setup guide

Set up Beekeeper 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 Beekeeper 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="Beekeeper_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Beekeeper 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 Beekeeper. 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

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Common questions about Beekeeper MCP in AutoGen

Agents pass messages back and forth, challenging conclusions and refining plans. They only execute the tool once they reach a consensus.

Yes, the MCP adapter converts the tools automatically for your agents. They use the Beekeeper functions just like any other built-in capability.

We enforce strict isolation within the Vinkius sandbox. Your user data and message logs are never exposed to external agents outside your defined conversation.

You just need the MCP server URL and the autogen-ext package. The adapter handles the schema conversion automatically, so you can start immediately.

The server manages all authentication internally. You provide one endpoint token, and the system handles the rest securely.

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