How to Use the Cyberimpact MCP in AutoGen

Q: How do I configure AutoGen to use Cyberimpact tools?

Install the autogen-extmcp package. Fetch the tool definitions using mcpservertools with your Vinkius HTTP endpoint, then pass them directly into your AssistantAgent constructor.

Q: Do AutoGen agents know if a Cyberimpact mailing was created successfully?

The API returns a success payload after createmailing executes. The execution agent reads this response and informs the rest of the chat group that the task is complete.

Deploy AutoGen multi-agent squads via this MCP Server to debate and manage your Cyberimpact email strategy.

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Connect Cyberimpact MCP to AutoGen

Create your Vinkius account to connect Cyberimpact 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 Cyberimpact with AutoGen

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Perplexity

Multi-Agent Campaign Negotiation

The `create_mailing` and `list_templates` tools become actions your agents negotiate over before executing. A copywriter agent drafts the email while a compliance agent reviews the content against your brand guidelines. Only after both agents reach a consensus does the system actually call the API to stage the campaign. This debate mechanism prevents half-baked newsletters from ever reaching your production account.

Consensus-Driven List Management

Processing contact removals requires deliberation when using `unsubscribe_member` or `delete_member`. A data hygiene agent flags unengaged users, while a sales agent argues to keep them based on recent CRM activity. They exchange messages until a final decision is reached. Once agreed, the execution agent fires the tool to remove the contact, making sure no valuable leads get deleted by a single flawed prompt.

AutoGen MCP Server Audience Building

Structuring your audience involves calling `create_group` and `add_member_to_group` after analyzing the raw contact list. Your analytical agents pull data via `list_members` and argue over the optimal segmentation strategy. One agent pushes for granular, highly specific groups while another advocates for broader, easier-to-manage lists. The resulting group structure reflects a balanced, well-reasoned approach rather than a random guess.

Setup guide

Set up Cyberimpact 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 Cyberimpact 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="Cyberimpact_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Install the autogen-ext[mcp] package. Fetch the tool definitions using mcp_server_tools with your Vinkius HTTP endpoint, then pass them directly into your AssistantAgent constructor.

You assign the tools to specific execution agents. The debate happens in plain text, and only the designated agent actually fires the API requests.

The McpToolAdapter handles schema conversion automatically. If an agent hallucinates a parameter, the tool returns an error, prompting the agents to discuss the failure and try again.

The API returns a success payload after create_mailing executes. The execution agent reads this response and informs the rest of the chat group that the task is complete.

Your agents process sensitive email addresses and campaign drafts. We run the server on ephemeral infrastructure where the entire execution environment is wiped clean the millisecond the HTTP request resolves.

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