DoubleTick MCP Server for LangChainGive LangChain instant access to 6 tools to Create Contact, Get Message Status, List Contacts, and more
LangChain is the leading Python framework for composable LLM applications. Connect DoubleTick through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
Ask AI about this App Connector for LangChain
The DoubleTick app connector for LangChain is a standout in the Productivity category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"doubletick-alternative": {
"transport": "streamable_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,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using DoubleTick, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About DoubleTick MCP Server
Connect your DoubleTick account to any AI agent and take full control of your official WhatsApp Business marketing and sales workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with DoubleTick through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Template Orchestration — List and manage approved WhatsApp message templates, including retrieving detailed metadata about languages and categories programmatically
- High-Engagement Messaging — Programmatically send template messages with dynamic placeholders to coordinate personalized customer outreach at scale
- Delivery Intelligence — Monitor real-time status (sent, delivered, read) for all messages to maintain high-fidelity communication oversight
- Contact Lifecycle — Programmatically create and manage your WhatsApp contact list to maintain an organized and segmented audience
- Group & Team Visibility — Access your directory of WhatsApp groups to understand team collaboration environments directly through your agent
The DoubleTick MCP Server exposes 6 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 6 DoubleTick tools available for LangChain
When LangChain connects to DoubleTick through Vinkius, your AI agent gets direct access to every tool listed below — spanning doubletick, whatsapp-business-api, whatsapp-automation, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a new contact
Check message delivery status
List WhatsApp contacts
List WhatsApp groups
List WhatsApp templates
Pass placeholders as a JSON string. Send a WhatsApp template message
Connect DoubleTick to LangChain via MCP
Follow these steps to wire DoubleTick into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the DoubleTick MCP Server
LangChain provides unique advantages when paired with DoubleTick through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine DoubleTick MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across DoubleTick queries for multi-turn workflows
DoubleTick + LangChain Use Cases
Practical scenarios where LangChain combined with the DoubleTick MCP Server delivers measurable value.
RAG with live data: combine DoubleTick tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query DoubleTick, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain DoubleTick tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every DoubleTick tool call, measure latency, and optimize your agent's performance
Example Prompts for DoubleTick in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with DoubleTick immediately.
"List all my approved WhatsApp templates in DoubleTick."
"Send the 'order_update' template to +123456789 with value 'Shipped'."
"Check the delivery status for message ID 'msg_123'."
Troubleshooting DoubleTick MCP Server with LangChain
Common issues when connecting DoubleTick to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersDoubleTick + LangChain FAQ
Common questions about integrating DoubleTick MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.