How to Use the DoubleTick MCP in LangChain

Q: How do I send a template message using DoubleTick in LangChain?

You call sendtemplatemessage within your chain by passing the template variables as a JSON string. Your LangChain agent automatically parses the arguments, formats the payload, and executes the tool.

Q: Can LangChain agents check if a DoubleTick message was delivered?

Yes, your agent can use getmessagestatus to track delivery in real-time. You can trace this entire tool execution inside LangSmith to see exactly when the status changed from sent to delivered.

Q: How does the DoubleTick MCP Server handle contact creation in LangChain?

Your agent invokes createcontact when a lead meets your qualification criteria. The tool registers the new phone number directly in your DoubleTick account, making it immediately available for template campaigns.

Q: Can I group my WhatsApp contacts dynamically with this setup?

Absolutely, your agent can run listgroups to retrieve your active WhatsApp groups, then use that data to segment who receives specific templates. This keeps your outreach targeted and reduces block rates.

Let your LangChain agents run WhatsApp outreach campaigns and manage your sales inbox on autopilot.

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Connect DoubleTick MCP to LangChain

Create your Vinkius account to connect DoubleTick 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 DoubleTick with LangChain

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Perplexity

Build LangChain WhatsApp campaigns

Running the DoubleTick MCP Server gives your LangChain agents the ability to execute complex messaging sequences without manual intervention. By chaining `list_templates` to pull approved templates and immediately firing `send_template_message`, your agent handles the entire outreach flow in a single run. You can track the progress of these runs through LangSmith. If a message fails, the agent inspects the output, checks the status with `get_message_status`, and decides whether to retry or flag the contact for manual follow-up.

Sync and qualify leads on the fly

Your LangChain CRM chains get a direct link to your WhatsApp database when you hook up this DoubleTick MCP Server. When a new lead qualifies in your LangChain pipeline, the agent calls `create_contact` to add them to your WhatsApp database instantly. The agent can also fetch existing prospects using `list_contacts` to prevent duplicate entries. This keeps your data clean and ensures your sales team never sends the same introductory template twice.

Manage customer groups dynamically

Managing WhatsApp groups gets a lot easier once the DoubleTick MCP Server exposes your active chats to LangChain routing chains. Your agent runs `list_groups` to find the right customer segment and coordinates targeted template blasts based on recent user activity. This turns static group chats into active sales channels. Because LangChain supports hundreds of database integrations, your agent can cross-reference group lists with your SQL databases before sending a single message.

Setup guide

Set up DoubleTick 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 DoubleTick 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({
    "doubletick-alternative-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 DoubleTick 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 DoubleTick. 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 DoubleTick MCP in LangChain

You call `send_template_message` within your chain by passing the template variables as a JSON string. Your LangChain agent automatically parses the arguments, formats the payload, and executes the tool.

Yes, your agent can use `get_message_status` to track delivery in real-time. You can trace this entire tool execution inside LangSmith to see exactly when the status changed from sent to delivered.

Your agent invokes `create_contact` when a lead meets your qualification criteria. The tool registers the new phone number directly in your DoubleTick account, making it immediately available for template campaigns.

Absolutely, your agent can run `list_groups` to retrieve your active WhatsApp groups, then use that data to segment who receives specific templates. This keeps your outreach targeted and reduces block rates.

All contact details and message histories processed by the server run inside isolated Vinkius sandboxes. We do not store your WhatsApp contacts or template strings on our servers; they are piped directly to the API and wiped instantly.

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