How to Use the Wati MCP in AutoGen

Q: Can AutoGen manage WhatsApp contacts effectively?

Yes. Agents can read contact lists via listwhatsappcontacts and use that data in their debate process to validate whether communication is appropriate before calling the messaging APIs.

Facilitate consensus decisions with AutoGen's multi-agent debate powered by Wati MCP Server tools.

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Create your Vinkius account to connect Wati 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 Wati with AutoGen

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Perplexity

Determine messaging strategy using the MCP Server

You can build a negotiation where one agent reviews contact details via `get_whatsapp_contact_details`. A second agent then debates whether to use a free-text message or an approved template, leading to a consensus decision on which function to call. This process mimics real-world review cycles, ensuring the right action is taken before sending.

Audit messaging templates with AutoGen

When multiple agents need to send messages, they can use `list_whatsapp_templates` as a resource. They debate which template best meets the current goal—for instance, one agent might flag it as too generic while another argues for its compliance. This consensus-driven approach prevents accidental or inappropriate messaging.

Contextualize contact actions with AutoGen

Agents use `list_whatsapp_contacts` and then cross-reference that list against the results of `get_whatsapp_chat_history`. The agents deliberate: Is this a cold lead? Was there recent activity? Based on that debate, they decide if any action is necessary. The outcome is a highly vetted plan of action.

Setup guide

Set up Wati 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 Wati 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="Wati_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Wati data")
    print(result.messages[-1].content)

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Common questions about Wati MCP in AutoGen

The MCP Server tools are passed to the AssistantAgent constructor. The agents then use their inherent debating structure to determine which tool, like `send_template_message`, is required to reach a decision.

The multiple autonomous agents discuss the goal and the available tools. They challenge assumptions until they converge on a single, agreed-upon tool call or final answer.

Yes. Agents can read contact lists via `list_whatsapp_contacts` and use that data in their debate process to validate whether communication is appropriate before calling the messaging APIs.

It's designed for complexity. If an action requires checking historical logs (`get_whatsapp_chat_history`) and then deciding on a message type, AutoGen facilitates that multi-agent deliberation.

The server handles contact phone numbers and message templates. Because agents debate the appropriate use of this sensitive information, it adds an extra layer of programmatic review before any action is taken.

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