How to Use the PushEngage MCP in LangChain

Build intelligent notification pipelines in LangChain by chaining PushEngage tools to automate visitor re-engagement.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect PushEngage MCP to LangChain

Create your Vinkius account to connect PushEngage to LangChain — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup PushEngage with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Automate visitor re-engagement chains

Connect your agent to `list_pushengage_triggers` to identify high-converting events. Chain these results directly into `send_pushengage_broadcast` to trigger targeted messages based on live user behavior. This workflow ensures your agent reacts to site activity without manual oversight. By linking tools, your chain maintains context across every notification sent to your audience.

Manage notification segments

Use `list_pushengage_segments` to grab active audience groups for your agent to analyze. Your LangChain agent can then filter these segments to determine the most relevant audience for specific campaign broadcasts. This approach avoids generic messaging by focusing on data-driven targeting. You define the logic, and the agent executes the segment selection before the broadcast tool fires.

Monitor API and subscriber health

Check the health of your integration using `check_pushengage_status` as a pre-condition in your chain. If the status is nominal, use `list_pushengage_subscribers` to feed active user counts into your agent's reasoning process. This step prevents failed broadcasts caused by downtime or stale configuration. Your agent gets a clear picture of system readiness before attempting to push any data to your site.

Setup guide

Set up PushEngage 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 PushEngage 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({
    "pushengage-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 PushEngage 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 PushEngage. 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.

Why Choose Vinkius

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Common questions about PushEngage MCP in LangChain

You build a chain where an agent evaluates your site triggers first. Once the agent identifies a need, it passes the data to the broadcast tool to execute the notification automatically.

Yes, you use the subscriber tool to fetch list data. The agent then processes this list to determine which segments should receive your next message.

It does. You can assign the server tools to a specific agent in your workflow, allowing it to handle notification tasks while other agents focus on content generation.

Your agent can call the status tool before initiating any broadcast. If the API returns errors, the agent can halt the chain to prevent broken requests.

We manage the connection through an isolated endpoint. Only the authorized tools touch your subscriber IDs and segment data, ensuring your internal list stays protected.

Use it with your favorite AI tools

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