How to Use the Sender.net MCP in LlamaIndex

Q: How do I set up the Sender.net MCP Server in LlamaIndex?

Run pip install llama-index-tools-mcp. Use BasicMCPClient with your endpoint, then wrap it in McpToolSpec to extract the async tools.

Q: Can LlamaIndex search through my Sender.net subscribers?

Your agent uses listsubscribers to pull the raw list. LlamaIndex can then embed those profiles into your index for semantic querying later.

Q: How do I restrict which Sender.net tools LlamaIndex uses?

Pass the allowedtools filter when configuring your agent. You might allow getcampaignanalytics but block deletesubscriber to prevent accidental deletions.

Q: Will LlamaIndex and Sender.net create new campaigns automatically?

Only if you give it permission. If you expose createcampaign, your FunctionAgent can draft and stage emails based on your RAG queries.

Index your Sender.net campaign data directly into LlamaIndex for semantic queries using this MCP Server.

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Connect Sender.net MCP to LlamaIndex

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Setup Sender.net with LlamaIndex

Ask AI about this MCP

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Claude

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Gemini

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Index Sender.net via MCP Server

LlamaIndex treats your mailing list like a live database. You hook up the server and run `list_email_campaigns`. The framework pulls all past broadcasts into memory. Those records become searchable nodes in your vector store. When you ask what worked last Black Friday, your agent queries the actual indexed API data. No hallucinations.

Query Live Subscriber Data

Static documents get stale fast. Your RAG application needs real-time context. It pulls active segments using `list_subscriber_groups` and `list_subscribers`. Unengaged users get filtered out when the agent checks `get_subscriber_details`. You get answers grounded in the exact state of your current audience.

Synthesize Campaign Analytics

Figuring out why conversions dropped takes time. The agent calls `get_campaign_analytics` to grab hard metrics. It embeds this performance data right alongside your HTML templates. Now you have a unified knowledge base. You ask your LlamaIndex setup to write a new email based on high-performing past sends. It knows exactly what to reference.

Setup guide

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

Run `pip install llama-index-tools-mcp`. Use `BasicMCPClient` with your endpoint, then wrap it in `McpToolSpec` to extract the async tools.

Your agent uses `list_subscribers` to pull the raw list. LlamaIndex can then embed those profiles into your index for semantic querying later.

Pass the `allowed_tools` filter when configuring your agent. You might allow `get_campaign_analytics` but block `delete_subscriber` to prevent accidental deletions.

Only if you give it permission. If you expose `create_campaign`, your FunctionAgent can draft and stage emails based on your RAG queries.

This integration handles raw email lists and user profiles. Vinkius isolates the connection in a zero-trust environment. The data only lives as long as your index requires it.

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