How to Use the Emarsys MCP in LlamaIndex

Q: Can LlamaIndex search across active Emarsys segments?

Yes, by calling listaudiencesegments, your LlamaIndex agent fetches all active segment filters and stores them as document nodes. You can then query these nodes semantically to identify which filters overlap or require updates.

Q: Can I use LlamaIndex to query trigger events?

The agent uses listtriggerevents to fetch all configured external triggers, converting them into searchable context. This allows your RAG application to map incoming customer actions to the correct automation triggers.

Index Emarsys campaign structures and list metadata directly into your LlamaIndex vector store for semantic search.

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Connect Emarsys MCP to LlamaIndex

Create your Vinkius account to connect Emarsys 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 Emarsys with LlamaIndex

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Index Emarsys setups using this MCP Server

The `list_email_campaigns` tool retrieves active campaign configurations, allowing your LlamaIndex pipeline to parse and index marketing structures directly into a vector database. Your agent queries this indexed data to answer complex questions about past campaign settings without calling the live API repeatedly. This setup eliminates hallucinations by grounding the agent's responses in actual Emarsys API outputs. The agent retrieves the exact campaign parameters using `get_campaign_details` to verify configurations against your documentation.

Query Emarsys contact lists in LlamaIndex

The `list_marketing_contact_lists` tool fetches the structure and settings of your marketing lists, which LlamaIndex then converts into queryable document nodes. Your agent performs semantic searches across list descriptions and metadata to find the correct target group for new initiatives. By coupling `get_contact_list_details` with LlamaIndex's retrieval-augmented generation, you can ask your agent which list matches a specific target profile. The agent cross-references the live API data with your internal vector store to find the best match.

Audit Emarsys programs with LlamaIndex agents

The `list_automation_programs` tool exposes active workflow configurations directly to LlamaIndex's function calling agents. Your agent reads the workflow trees, indexes the steps, and highlights gaps or redundancies in your automated marketing logic. This MCP Server turns raw API data into a searchable knowledge base. The agent uses `quick_engagement_volume_audit` to monitor campaign volumes and correlate those numbers with active automation structures stored in your index.

Setup guide

Set up Emarsys 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 Emarsys 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 Emarsys tools.",
)
response = await agent.run("List recent Emarsys 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 Emarsys. 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 Emarsys MCP in LlamaIndex

Connect the MCP Server using BasicMCPClient, load the tools with McpToolSpec, and pass them to your LlamaIndex agent. The agent calls list_email_campaigns to retrieve the configurations and indexes the resulting JSON payloads into your vector store.

Yes, by calling list_audience_segments, your LlamaIndex agent fetches all active segment filters and stores them as document nodes. You can then query these nodes semantically to identify which filters overlap or require updates.

LlamaIndex grounds its responses directly in the live JSON payloads returned by tools like get_emarsys_account_metadata. The agent relies strictly on the retrieved API schema rather than guessing your account setup.

The agent uses list_trigger_events to fetch all configured external triggers, converting them into searchable context. This allows your RAG application to map incoming customer actions to the correct automation triggers.

The MCP Server handles contact list metadata, campaign settings, and form configurations. Vinkius runs the server in an ephemeral, zero-trust sandbox, meaning contact list structures fetched via get_contact_list_details are processed in memory and never written to disk.

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