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How to Use the Listrak MCP in LlamaIndex

Index your Listrak customer data directly into LlamaIndex to create knowledge-augmented marketing agents.

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LlamaIndex

Connect Listrak MCP to LlamaIndex

Create your Vinkius account to connect Listrak to LlamaIndex 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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Ground Agents in Listrak Data

LlamaIndex turns the output of `list_sms_contacts` into a searchable vector index. Your agent doesn't just call the API; it understands your current subscriber base. This provides a grounded context for your queries. You get answers based on actual list state rather than generic marketing assumptions.

Query Your Listrak Campaigns

Retrieve historical campaign performance using `list_email_campaigns` and map it to your knowledge base. This lets your agent compare current results against past benchmarks. It makes your RAG pipeline smarter. You query the index for trends and receive responses backed by your specific API data.

Manage Listrak Subscriptions Semantically

Use `subscribe_to_sms_list` as part of a tool-augmented agent workflow. The agent checks the index first to see if the contact exists before taking action. This prevents duplicate entries and ensures your lists stay clean. You are building a system that understands the state of your audience.

Setup guide

Set up Listrak MCP in LlamaIndex

Prerequisites

  • Python 3.10+ installed
  • llama-index-tools-mcp package
  • Active Vinkius subscription with a valid endpoint token
  1. 1

    Install dependencies

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

  2. 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. 3

    Convert to LlamaIndex tools

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

  4. 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 Listrak tools.",
)
response = await agent.run("List recent Listrak data")

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Listrak. 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 Listrak MCP in LlamaIndex

The MCP tools fetch the raw data, which is then processed by your LlamaIndex pipelines. It converts API responses into searchable nodes for your agent.
Yes, you use the MCP tool spec to wrap the server. This exposes the functions as native tools for your agent to execute against the Listrak API.
Vinkius manages the secure connection to the Listrak servers. Your sensitive contact information stays within the ephemeral sandbox environment during execution.
You can call `send_transactional_email` through the agent if your logic permits. It executes the action immediately upon request.
Only the output you choose to index is stored in your vector store. This typically includes contact lists and campaign metadata.

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