How to Use the Campaign Monitor MCP in LlamaIndex

Q: How do I use the Campaign Monitor tools with a LlamaIndex agent?

Install llama-index-tools-mcp and instantiate the McpToolSpec with your Vinkius server URL. This spec object makes the Campaign Monitor tools available to your LlamaIndex agent for building RAG or query pipelines.

Q: Can LlamaIndex query my Campaign Monitor templates?

Yes. The listemailtemplates tool is included. You can use it to pull the names and IDs of your templates, index them, and then allow your agent to find the right template for a new campaign based on a natural language description.

Turn your Campaign Monitor data into a searchable knowledge base for your LlamaIndex RAG apps.

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Connect Campaign Monitor MCP to LlamaIndex

Create your Vinkius account to connect Campaign Monitor 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 Campaign Monitor with LlamaIndex

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Index Campaign Performance Data

This server connects LlamaIndex directly to your live Campaign Monitor data. You can build an agent that periodically calls `list_campaigns` and `get_campaign_performance`, then automatically indexes the results into a vector store. It’s a living archive of your marketing efforts. Once indexed, you can ask questions in natural language. Instead of manually digging through the Campaign Monitor UI, you just ask your LlamaIndex app, "Which Q2 campaign had the best click-through rate?" The answer comes from your own data, not a guess.

Build a RAG App on Your Contact Lists

Go beyond simple list management. Use the `list_contact_lists` and `list_subscribers` tools to create a detailed index of your audience. This turns raw subscriber data into a queryable resource for your agent. Now you can build powerful RAG applications that answer complex questions. Ask things like, "Summarize the subscriber overlap between the 'Newsletter' and 'Beta Testers' lists," and get a grounded answer based on the actual data pulled by the MCP tools.

Ground Your Agent in Real-Time Data

Hallucinations happen when an agent doesn't have the right information. This Campaign Monitor MCP Server solves that by giving your LlamaIndex agent a direct line to the ground truth. Before answering a question, it can fetch fresh data. For example, if you ask, "How many subscribers do we have on the main list?", the agent doesn't have to guess. It can call `get_contact_list` to get the list ID and then `list_subscribers` to get a live count. Your answers are always based on what's actually in your account right now.

Setup guide

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

Install `llama-index-tools-mcp` and instantiate the `McpToolSpec` with your Vinkius server URL. This spec object makes the Campaign Monitor tools available to your LlamaIndex agent for building RAG or query pipelines.

Yes. The `list_email_templates` tool is included. You can use it to pull the names and IDs of your templates, index them, and then allow your agent to find the right template for a new campaign based on a natural language description.

That's the point. You can index your Campaign Monitor data alongside documents from Notion, messages from Slack, or data from a database. LlamaIndex queries across all of them to give your agent a complete picture before it acts.

It saves you from writing and maintaining the API connection code. The MCP server provides clean, pre-defined tools that plug right into LlamaIndex. You can focus on building your index and query logic, not on dealing with Campaign Monitor's API authentication and endpoints.

The MCP server itself provides a secure, ephemeral connection to fetch the data. Once you use LlamaIndex to put that data—like campaign performance stats or subscriber details—into a vector store, the security of that database is your responsibility. The transport is secure; the storage is up to you.

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