How to Use the PushEngage MCP in LlamaIndex

Index your PushEngage data into LlamaIndex to build RAG apps that ground your notifications in historical campaign performance.

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Connect PushEngage MCP to LlamaIndex

Create your Vinkius account to connect PushEngage to LlamaIndex — 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 LlamaIndex

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Ground notifications in past data

Fetch historical campaigns using `list_pushengage_notifications` and feed the output into your LlamaIndex vector store. Your agent can then query this index to see what messaging worked best in previous months. This adds a layer of intelligence to your current campaigns. Instead of guessing, the agent references actual performance data to craft better notification content.

Query segments for smarter targeting

Index your `list_pushengage_segments` results so your agent understands your audience breakdown. When you ask to target specific users, the agent retrieves the right segment IDs from your knowledge base. This creates a queryable map of your users. You no longer need to look up IDs manually, as the agent retrieves them from your indexed knowledge.

Track trigger effectiveness

Store the output of `list_pushengage_triggers` in your index to maintain a searchable record of active automation rules. Your agent references these rules to decide when a notification is appropriate. This keeps your automation logic transparent and accessible. The agent analyzes the triggers within your index to ensure every broadcast aligns with your current site strategy.

Setup guide

Set up PushEngage MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all PushEngage MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to PushEngage tools.",
)
response = await agent.run("List recent PushEngage data")

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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.

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Common questions about PushEngage MCP in LlamaIndex

It indexes the tool outputs into a vector store. This allows your agent to perform semantic searches over your campaign history and subscriber segments.

You can pull the list of subscribers and add them to your index. This makes your subscriber data part of the agent's queryable knowledge base.

It integrates directly by providing tools that turn API responses into searchable documents. You simply add these tools to your agent's tool list.

They are retrieved via the listing tool and then embedded into your index. This preserves the context of your past messaging efforts.

Your subscriber records stay within your local index session. We provide the connection, but you control how the sensitive data is stored and retrieved.

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