How to Use the Drip MCP in LlamaIndex

Q: How does LlamaIndex index subscriber profiles from Drip?

LlamaIndex calls listsubscribers via the MCP Server to fetch subscriber metadata, email addresses, and tags. It then converts this JSON payload into document nodes and inserts them into your LlamaIndex vector store.

Q: Can I search my active Drip campaigns using LlamaIndex semantic search?

Yes, you query Drip campaign data by calling listcampaigns and loading the results into a LlamaIndex index. This allows your agent to answer natural language questions about which email series are currently running.

Index Drip subscriber data, tags, and workflows directly into LlamaIndex to build context-aware marketing RAG applications.

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Connect Drip MCP to LlamaIndex

Create your Vinkius account to connect Drip 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 Drip with LlamaIndex

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Semantic Search Over Drip Profiles

LlamaIndex indexes the raw outputs of `list_subscribers` and `get_subscriber` directly into your vector store for searching Drip profiles. Instead of writing complex SQL queries, your LlamaIndex agent searches this index using natural language to find specific Drip cohorts. The LlamaIndex agent retrieves the relevant Drip profiles, reviews their custom fields, and uses `tag_subscriber` to group them. This turns static Drip CRM data into a dynamic, queryable database that your LlamaIndex agent references.

RAG-Driven Campaign Auditing in LlamaIndex

You feed Drip campaign metrics into your LlamaIndex knowledge graphs to analyze email performance. The LlamaIndex agent uses `list_campaigns` to pull active Drip email series data and compares it against historical performance metrics. By analyzing this combined dataset, the LlamaIndex agent identifies underperforming Drip sequences. It then automatically calls `list_workflows` to map out the customer journey within LlamaIndex.

Context-Aware Automation via MCP Server

This MCP Server lets your LlamaIndex agent trigger `record_event` based on semantic context rather than rigid rules. When a user asks a question in LlamaIndex that signals high buying intent, the agent immediately runs `record_event` to log the interaction in Drip. From there, the LlamaIndex agent checks the user's current Drip status and uses `start_workflow` to put them on a fast-track sales sequence. This ensures your Drip marketing automation responds to the actual meaning behind a LlamaIndex query.

Setup guide

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

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Common questions about Drip MCP in LlamaIndex

LlamaIndex calls `list_subscribers` via the MCP Server to fetch subscriber metadata, email addresses, and tags. It then converts this JSON payload into document nodes and inserts them into your LlamaIndex vector store.

Yes, you query Drip campaign data by calling `list_campaigns` and loading the results into a LlamaIndex index. This allows your agent to answer natural language questions about which email series are currently running.

The LlamaIndex agent performs a semantic search to identify subscribers who match a specific criteria, then iterates through them using `tag_subscriber` or `remove_tag` to update their Drip profiles.

Yes, you configure the LlamaIndex query engine to route specific requests to the `start_workflow` tool. If the retrieved context indicates a subscriber needs to enter a Drip campaign, the tool executes the action instantly.

Yes, because all MCP tool calls to retrieve subscriber profiles are routed through an ephemeral V8 sandbox. Your customer emails, tags, and custom fields are processed locally in memory and never stored on external LLM servers.

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