MoEngage MCP Server for LangChainGive LangChain instant access to 13 tools to Check Moengage Status, Get Campaign, Get Campaign Stats, and more
GDPR Free for SubscribersLangChain is the leading Python framework for composable LLM applications. Connect MoEngage 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 MCP Server for LangChain
The MoEngage MCP Server for LangChain is a standout in the Growth Engine category — giving your AI agent 13 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
Geminiimport 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({
"moengage": {
"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 MoEngage, 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 MoEngage MCP Server
Connect your MoEngage account to any AI agent and manage customer engagement through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with MoEngage through native MCP adapters. Connect 13 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
- User Management — Create/update user attributes and device data
- Event Tracking — Track custom user events and behaviors
- Push Notifications — Trigger transactional and marketing push messages
- Campaign Management — Launch and pause multi-channel campaigns
- Analytics — Retrieve campaign performance and user statistics
The MoEngage MCP Server exposes 13 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 13 MoEngage tools available for LangChain
When LangChain connects to MoEngage through Vinkius, your AI agent gets direct access to every tool listed below — spanning customer-engagement, push-notifications, behavioral-analytics, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Check moengage status on MoEngage
Verify connectivity
Get campaign on MoEngage
Get campaign details
Get campaign stats on MoEngage
Get campaign stats
Get customer on MoEngage
Get customer details
Get segment on MoEngage
Get segment details
List campaigns on MoEngage
List campaigns
List segments on MoEngage
List segments
Search customers on MoEngage
Search customers
Send push on MoEngage
Send push notification
Track event on MoEngage
Track an event
Track events bulk on MoEngage
Track events in bulk
Update device on MoEngage
Update device info
Upsert customer on MoEngage
Create or update customer
Connect MoEngage to LangChain via MCP
Follow these steps to wire MoEngage into LangChain. The entire setup takes under two minutes — your credentials stay safe behind 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 MoEngage MCP Server
LangChain provides unique advantages when paired with MoEngage through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine MoEngage 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 MoEngage queries for multi-turn workflows
MoEngage + LangChain Use Cases
Practical scenarios where LangChain combined with the MoEngage MCP Server delivers measurable value.
RAG with live data: combine MoEngage tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query MoEngage, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain MoEngage tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every MoEngage tool call, measure latency, and optimize your agent's performance
Example Prompts for MoEngage in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with MoEngage immediately.
"Show performance for the 'Spring Sale Push' campaign."
"Send a transactional push notification to user 8901."
"Track a 'Subscription Upgraded' event for user Sarah."
Troubleshooting MoEngage MCP Server with LangChain
Common issues when connecting MoEngage to LangChain through Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMoEngage + LangChain FAQ
Common questions about integrating MoEngage 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.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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