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How to Use the Mailify (Sarbacane) MCP in LlamaIndex

Index your Mailify (Sarbacane) marketing metrics and contact lists into LlamaIndex for grounded, real-time RAG queries.

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Connect Mailify (Sarbacane) MCP to LlamaIndex

Create your Vinkius account to connect Mailify (Sarbacane) 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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RAG for Mailify (Sarbacane) Campaigns

You need marketing answers based on actual performance, not guesses. By connecting the `list_email_campaigns` and `get_campaign_details` tools, LlamaIndex pulls your historical broadcast data directly into a queryable vector store. When someone asks about last quarter's engagement, the agent avoids hallucinating. It runs `get_campaign_performance`, retrieves the hard click rates, and synthesizes an answer grounded entirely in your live API data.

Index Address Books with this MCP Server

Context matters when segmenting users. The `list_address_books` and `get_address_book_details` tools allow your LlamaIndex application to map out exactly how your audience is divided before generating new content. Your agent reads the metadata for every list. If a user asks which segment receives the newsletter, the system queries the index, finds the right list ID, and returns the exact subscriber count.

Ground Answers in Live Contact Data

Sometimes you need to know exactly who is on a specific list. LlamaIndex uses `list_book_contacts` to fetch the raw subscriber data and embed it into your knowledge base. You can then ask your agent if a specific VIP client received a recent promotion. It checks the indexed contacts, verifies their presence, and confirms their status without you ever logging into the marketing dashboard.

Setup guide

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

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

Initialize a `BasicMCPClient` and wrap it with `McpToolSpec`. Then call `await mcp_tool_spec.to_tool_list_async()` to pass the MCP tools to your FunctionAgent.
Yes, the agent can execute writes. If configured with allowed tools, it can run `update_book_contact` or `add_contact_to_book` based on user instructions.
That depends on how you build your RAG pipeline. You can index the output of `get_campaign_performance` for fast retrieval or fetch it live during each query.
You can expose `delete_book_contact` to your agent. Make sure you implement confirmation steps in your UI so the agent avoids removing subscribers accidentally.
The integration processes email addresses and engagement stats entirely in memory. The LlamaIndex MCP client talks directly to the API, meaning no third party intercepts your contact lists.

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