How to Use the Gallabox MCP in AutoGen

Build multi-agent WhatsApp workflows in AutoGen where agents debate routing and template selection before sending.

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Connect Gallabox MCP to AutoGen

Create your Vinkius account to connect Gallabox 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 Gallabox with AutoGen

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Debate WhatsApp template selection in AutoGen

The `send_whatsapp_template` and `list_message_templates` tools allow your AutoGen agents using this MCP Server to collaborate on choosing the best template for a customer scenario. A template agent suggests a message, a compliance agent checks it against approved guidelines, and a sender agent executes the call. This collaborative debate prevents your system from sending incorrect or unapproved templates to customers. You avoid account bans by ensuring every automated broadcast is verified by multiple specialized agents before execution.

Coordinate multi-agent support routing over WhatsApp

The `list_support_teams` and `get_chat_details` tools let your AutoGen agents negotiate which human team should handle a complex WhatsApp conversation. A triage agent analyzes the chat history while a routing agent matches the issue to active teams. Once the agents reach a consensus on the best team, they update the chat state or hand it off. This eliminates manual triage and ensures complex technical issues go to engineers while billing queries go to finance.

Resolve contact conflicts with this MCP Server

The `list_whatsapp_contacts` and `get_contact_details` tools give your AutoGen agents the data needed to reconcile duplicate customer profiles. One agent flags conflicting phone numbers while another queries the messaging database to merge the records. By debating which contact profile is the most up-to-date, your agents maintain a clean address book. This consensus-driven cleaning keeps your communication channel free of duplicate threads and incorrect contact names.

Setup guide

Set up Gallabox 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 Gallabox 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="Gallabox_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

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

AutoGen agents use a consensus step where the executor agent checks `list_active_chats` before calling `send_whatsapp_text`. If another agent just sent a message, the action is blocked.

Yes, you can assign the MCP Server tools selectively. For example, you can give the template tools only to your marketing agent while restricting the support tools to your triage agent.

Your manager agent can query the MCP Server to diagnose connection issues. If the check fails, the agents can pause operations and alert a human moderator instead of retrying blindly.

The integration uses the Streamable HTTP transport via the Vinkius managed endpoint. This allows your multi-agent system to call the tools asynchronously during group chats.

No, the templates and contact lists are retrieved in real-time and kept only in your active agent memory. Vinkius runs the server in an isolated, zero-trust sandbox to guarantee no data is cached.

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