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How to Use the UTM Campaign Builder MCP in LlamaIndex

Index marketing link results with LlamaIndex for knowledge-augmented search.

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Connect UTM Campaign Builder MCP to LlamaIndex

Create your Vinkius account to connect UTM Campaign Builder 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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Store and query UTM URLs using the MCP Server

The `build_utm_url` tool safely constructs and encodes marketing tracking links, which you can then index into your vector store. When an agent builds a link, LlamaIndex captures it as searchable data. This means you don't just run the tool; you save its output so you can query past campaigns months later.

Retrieve campaign link logic with LlamaIndex

You pass required inputs—base URL, source, medium—to `build_utm_url`. The resulting flawless link is then stored and becomes part of your knowledge base. You can ask questions like, 'What was the UTM link for our Q3 Facebook ads?' LlamaIndex grounds its answer in the actual API data provided by this MCP Server.

Build reliable marketing content with LlamaIndex and MCP Server

The tool allows optional parameters (`utm_campaign`, `utm_term`, etc.), giving your agent flexibility. When you build a link for a specific product launch, that complete URL is indexed. It prevents hallucinations because the output of `build_utm_url` is concrete data, not just text generation.

Setup guide

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

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Common questions about UTM Campaign Builder MCP in LlamaIndex

Instead of forgetting past campaign details, you let the MCP Server build the links and index them. This lets your agent query historical UTM data accurately against a searchable knowledge base.
The core inputs for `build_utm_url` remain consistent: the base landing page URL, the `utm_source`, and the `utm_medium`. These three pieces of data start every link.
Yes. You run the tool via your RAG application, storing each generated URL. This turns transient API calls into persistent knowledge you can search and reference later.
It works great. You build the necessary links using `build_utm_url` and then index them. Your agent can retrieve all relevant campaign tracking data from your unified index.
The server processes standard URL query strings containing marketing parameters (`utm_source`, `utm_medium`, etc.). This data is public metadata, not sensitive personal information.

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