How to Use the WA Smart Business MCP in AutoGen

Q: What data does AutoGen use from WA Smart Business?

It uses all tool outputs: contact lists, group structures (listgroups), and template definitions. These outputs become the evidence used by the agents during their debate to reach a decision.

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Connect WA Smart Business MCP to AutoGen

Create your Vinkius account to connect WA Smart Business 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 WA Smart Business with AutoGen

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Claude

Perplexity

Debated Messaging Strategy

You set up competing agents—one might be the 'Compliance Agent' that checks `list_templates` for policy violations. Another might be the 'Execution Agent' that tries to run `send_message`. They debate which action is best, leading to a consensus decision. This process forces deliberation and negotiation between multiple viewpoints before any API call is made.

Multi-Agent Contact Verification

Need to validate contacts? You can have one agent run `list_contacts` for scope, while a second agent uses `get_contact` on specific records. They argue over the completeness or accuracy of the data until they agree on a final, verified list. This is ideal when the answer requires cross-checking multiple sources and perspectives.

Structured Group Setup Consensus

If you're figuring out how to structure a campaign, you can deploy agents to discuss options. One agent might suggest listing groups using `list_groups`, while another argues for creating new ones. They iterate until they achieve consensus on the optimal group structure. This is superior to linear scripting because it simulates human discussion and negotiation.

Setup guide

Set up WA Smart Business 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 WA Smart Business 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="WA Smart Business_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent WA Smart Business 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="WA Smart Business_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent WA Smart Business 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 WA Smart Business. 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 WA Smart Business MCP in AutoGen

AutoGen lets multiple agents debate business actions. Instead of the code simply running a tool, the agents discuss whether they *should* run `send_message` or if they need more data first, improving decision quality.

Yes. You build systems where the conclusion isn't obvious and requires deliberation between competing perspectives—like a security agent flagging risks while an execution agent pushes for speed. It handles ambiguity.

It uses all tool outputs: contact lists, group structures (`list_groups`), and template definitions. These outputs become the evidence used by the agents during their debate to reach a decision.

It is. Direct calls are single actions. AutoGen adds a layer of intelligence—it requires consensus and reasoning, meaning the final action is vetted by multiple simulated experts.

You can set up agents where one agent retrieves contacts using `get_contact` and another reviews that data for compliance issues before the final message is sent. The debate ensures quality.

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