How to Use the Iterable MCP in LlamaIndex

Q: How is customer email and campaign setup data secured?

All API requests for user profiles via getuser run inside ephemeral sandbox environments. The server handles the token exchange securely, ensuring that sensitive email addresses and campaign structures are never exposed to public networks.

Index live Iterable campaign metrics and user data into your LlamaIndex vector store via MCP.

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Connect Iterable MCP to LlamaIndex

Create your Vinkius account to connect Iterable 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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Setup Iterable with LlamaIndex

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Build a searchable knowledge base of your marketing assets

Your LlamaIndex pipeline can index active marketing templates by calling `list_templates` and storing the results. This lets you query your entire content library using semantic search to find similar messaging styles. Instead of searching through a web UI, your RAG setup queries the vector store to see what copy worked. It uses the output of `list_message_types` to organize your templates by their actual functional categories.

Ground LlamaIndex queries in real-time MCP Server metrics

Stop guessing how your campaigns are performing. By connecting this MCP Server, LlamaIndex can fetch live data using `get_campaign_metrics` to answer specific questions about subscriber engagement. Your queries get answered using actual performance data rather than outdated spreadsheet exports. The index combines these metrics with active lists from `list_lists` to give you a clear picture of audience behavior.

Map automated workflows to user profiles

Connecting these tools lets your index link active automation sequences with subscriber profiles. By calling `list_workflows` and `get_user`, LlamaIndex maps out which users are currently moving through specific message paths. This mapping helps you identify bottlenecks in your lifecycle marketing. You can query the index to find out why a specific user group is receiving certain messages without digging through complex visual builders.

Setup guide

Set up Iterable 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 Iterable 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 Iterable tools.",
)
response = await agent.run("List recent Iterable data")

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Common questions about Iterable MCP in LlamaIndex

You use the llama-index-tools-mcp package to load the tools into your agent. The tool spec pulls campaign details via `list_campaigns` and indexes the returned JSON directly into your vector store.

Yes, you can use a function calling agent to retrieve profiles on demand. The agent calls `get_user` only when a user-specific query is made, avoiding the need to index your entire subscriber database.

The McpToolSpec automatically translates the server schemas into LlamaIndex tool definitions. This ensures your agent understands the inputs for tools like `get_campaign` and `list_webhooks` without manual mapping.

Yes, you can apply an allowed tools filter during initialization. If you only want to index structural data, you can limit the agent to `list_channels` and `list_message_types` while hiding user data.

All API requests for user profiles via `get_user` run inside ephemeral sandbox environments. The server handles the token exchange securely, ensuring that sensitive email addresses and campaign structures are never exposed to public networks.

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