How to Use the Avochato MCP in AutoGen

Q: Can AutoGen agents collaborate on sending an Avochato SMS?

Yes, one agent drafts the message while another executes sendmessage. They communicate in a shared group chat to finalize the text before sending.

Q: How do AutoGen agents search Avochato contacts?

The agents use listcontacts to search for existing profiles. They discuss the results to determine if they need to create a new record.

Let AutoGen agents debate and coordinate Avochato SMS broadcasts and customer contact updates.

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Connect Avochato MCP to AutoGen

Create your Vinkius account to connect Avochato 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 Avochato with AutoGen

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Coordinate SMS broadcasts via AutoGen agent consensus

The `create_broadcast` tool schedules bulk text campaigns only after your agents agree on the content. This MCP setup lets a copywriter agent draft the message, while a compliance agent reviews it for spam triggers. Once both agents reach consensus, the execution agent triggers the broadcast. Your team avoids accidental spam and keeps messaging campaigns aligned with brand guidelines.

Debate and verify contact updates using this MCP Server

The `update_contact` tool modifies customer profiles after your agents verify the incoming data. If a customer texts a new email, one agent flags the change while another checks it against existing records using `list_contacts`. This collaborative check prevents messy data overwrites. Your agents collaborate to keep the database accurate without requiring manual human oversight.

Manage conversational SMS queues autonomously

The `send_message` tool dispatches individual texts during active conversations with customers. An analysis agent reads incoming texts via `list_messages` and proposes a response. A supervisor agent reviews the draft before the final tool call occurs. This multi-agent review loop ensures high-quality customer interactions over SMS.

Setup guide

Set up Avochato 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 Avochato 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="Avochato_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

Use the MCP tool adapter from the AutoGen extensions package. Pass your Vinkius endpoint URL to fetch the tools and assign them to your assistant agent.

Yes, one agent drafts the message while another executes `send_message`. They communicate in a shared group chat to finalize the text before sending.

The agents use `list_contacts` to search for existing profiles. They discuss the results to determine if they need to create a new record.

Yes, this setup works perfectly in CLI and headless environments. The agents handle the conversational logic and tool execution in the background.

Yes, your credentials are encrypted and stored securely within the Vinkius MCP host infrastructure. The agents only interact with the exposed tools, never exposing your raw API keys or contact databases.

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