How to Use the WA Smart Business MCP in LangChain

Q: What data does WA Smart Business expose via LangChain?

It exposes contact details, group lists (listgroups), and message templates (listtemplates). This raw data feeds directly into your chain's context for processing.

Q: If I need to check contact status with WA Smart Business and LangChain?

You can use getcontact within your chain. The agent gets the current details, which you then pass into a subsequent tool call for further processing. It keeps the data flowing.

Build multi-step WA Smart Business workflows with LangChain.

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Connect WA Smart Business MCP to LangChain

Create your Vinkius account to connect WA Smart Business to LangChain 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 LangChain

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Multi-Step Messaging Chains

You can chain together multiple messaging steps. For example, an agent first runs `list_contacts` to verify recipients. Then, it passes that list into the `send_message` tool to send a campaign. The output of the contact list immediately becomes the input for the next step. This means your LangChain setup handles complex, ordered actions where one API call dictates the parameters for the next. It's full reasoning right out of the box.

Contact and Group Management Pipelines

Need to manage contacts in stages? You can build a pipeline that first calls `list_groups` to identify target communities. Next, it uses `get_contact` on specific members to pull required details. This structured approach ensures the agent has all necessary data points before attempting any action. This capability lets you model real-world business processes directly into your LangChain code, moving beyond simple single-step API calls.

Template and Agent Orchestration

The system supports multi-stage reasoning using tools like `list_templates` and `list_agents`. An agent can first check available templates to ensure compliance, then use `create_contact` if a new recipient is found. The workflow maintains context across these varied operations. This gives you the control needed to build highly specific automation chains that handle diverse business logic.

Setup guide

Set up WA Smart Business MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes WA Smart Business tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "wa-smart-business-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent WA Smart Business transactions"
    })
    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 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 LangChain

LangChain uses the MCP Server tools to execute actions. When you call a tool like `send_message`, the agent gets real-time feedback and can use that output data in subsequent steps, making it much more powerful than simple sequential calls.

Yeah, absolutely. You build these multi-step pipelines where the agent decides which tool to call and in what precise order based on intermediate results from previous calls. It's designed for that kind of complex decision making.

It exposes contact details, group lists (`list_groups`), and message templates (`list_templates`). This raw data feeds directly into your chain's context for processing.

It moves you past simple API wrappers. You build reasoning engines that decide the best sequence of calls—for instance, checking contacts before sending a message—which is what makes it so useful.

You can use `get_contact` within your chain. The agent gets the current details, which you then pass into a subsequent tool call for further processing. It keeps the data flowing.

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