How to Use the Loops MCP in LlamaIndex

Q: Can I query Loops transactional logs using LlamaIndex?

Yes, you use listtransactionalemails to retrieve recent logs and load them into a LlamaIndex document store. From there, your agent performs semantic search to locate specific emails.

Q: How does LlamaIndex use Loops contact data for RAG?

The agent calls findcontact to pull the active user's profile, including their user group. This profile data is injected into the prompt context, ensuring the RAG pipeline generates personalized answers.

Q: How do I subscribe users to Loops lists from LlamaIndex?

Your agent first calls listmailinglists to find the correct list ID. Then, it triggers createcontact with the user's email and the target list ID to complete the subscription.

Q: Can the LlamaIndex agent verify my API key is active?

The agent runs testapikey during initialization to confirm the connection is live. If the check fails, the index setup halts to prevent broken tool calls during query runs.

Index Loops contact data and email logs into LlamaIndex to ground your agent responses in real marketing metrics using our MCP Server.

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Connect Loops MCP to LlamaIndex

Create your Vinkius account to connect Loops 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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Index Loops email logs into LlamaIndex

`list_transactional_emails` pulls your recent Loops transactional history directly into LlamaIndex vector stores to ground your agent's knowledge. Your LlamaIndex RAG pipeline queries this index to answer user questions about sent Loops messages without hallucinating delivery details. Basically, the LlamaIndex agent runs semantic search over the retrieved Loops logs, matching user queries against actual template names. That's how you stop LlamaIndex support bots from making up Loops delivery dates or status updates.

Query Loops mailing lists via LlamaIndex MCP Server

`list_mailing_lists` exposes your current Loops marketing segments to LlamaIndex so your agent can recommend the right list to join. The LlamaIndex agent reads the available Loops lists, matches them to user preferences, and subscribes them accurately. By indexing these Loops lists, the LlamaIndex agent knows exactly which segments exist without hardcoding. It uses this LlamaIndex context to decide whether to call `create_contact` or update an existing Loops record.

Find and update Loops contacts using LlamaIndex lookups

`find_contact` retrieves specific subscriber profiles in Loops to feed live contact metadata into your LlamaIndex query context. The LlamaIndex agent uses this Loops profile data to personalize its responses based on the user's group or sign-up date. When a user requests a profile change, the LlamaIndex agent executes `update_contact` with the updated Loops variables. This keeps the LlamaIndex index and your Loops database synchronized in real time via the MCP integration.

Setup guide

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

Yes, you use `list_transactional_emails` to retrieve recent logs and load them into a LlamaIndex document store. From there, your agent performs semantic search to locate specific emails.

The agent calls `find_contact` to pull the active user's profile, including their user group. This profile data is injected into the prompt context, ensuring the RAG pipeline generates personalized answers.

Your agent first calls `list_mailing_lists` to find the correct list ID. Then, it triggers `create_contact` with the user's email and the target list ID to complete the subscription.

The agent runs `test_api_key` during initialization to confirm the connection is live. If the check fails, the index setup halts to prevent broken tool calls during query runs.

Emails and user group fields are processed in memory within Vinkius's zero-trust environment. No contact data is stored on our servers, and all API calls require a single, encrypted endpoint token.

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